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Particle Filter with Stable Embedding for State Estimation of the Rigid Body Attitude System on the Set of Unit Quaternions | https://ieeexplore.ieee.org/document/10610922/ | [
"Hee-Deok Jang",
"Jae-Hyeon Park",
"Dong Eui Chang",
"Hee-Deok Jang",
"Jae-Hyeon Park",
"Dong Eui Chang"
] | This paper presents a novel method for state estimation of rigid body attitude system evolving on the manifold S3, which is crucial in robotics and drone applications. We introduce a particle filter with stable embedding that extends the system into Euclidean space while ensuring stability of the manifold. Our particle filter with stable embedding enables accurate state estimation by maintaining e... |
End-to-end Reinforcement Learning for Time-Optimal Quadcopter Flight | https://ieeexplore.ieee.org/document/10611665/ | [
"Robin Ferede",
"Christophe De Wagter",
"Dario Izzo",
"Guido C.H.E. de Croon",
"Robin Ferede",
"Christophe De Wagter",
"Dario Izzo",
"Guido C.H.E. de Croon"
] | Aggressive time-optimal control of quadcopters poses a significant challenge in the field of robotics. The state-of-the-art approach leverages reinforcement learning (RL) to train optimal neural policies. However, a critical hurdle is the sim-to-real gap, often addressed by employing a robust inner loop controller —an abstraction that, in theory, constrains the optimality of the trained controller... |
Robust Control for Bidirectional Thrust Quadrotors under Instantaneously Drastic Disturbances | https://ieeexplore.ieee.org/document/10611241/ | [
"Zujian Chen",
"Shaolin Mo",
"Botao Zhang",
"Jiyu Li",
"Hui Cheng",
"Zujian Chen",
"Shaolin Mo",
"Botao Zhang",
"Jiyu Li",
"Hui Cheng"
] | Quadrotors may crash and cause severe accidents under instantaneously drastic disturbances. To mitigate the effect of such disturbances, these critical issues should be considered: efficient disturbance observation and compensation, full attitude controllability, and instant output power generation of the quadrotor. In this paper, to keep the quadrotor stable even under suddenly drastic disturbanc... |
A Multi-modal Hybrid Robot with Enhanced Traversal Performance* | https://ieeexplore.ieee.org/document/10609980/ | [
"Zhipeng He",
"Na Zhao",
"Yudong Luo",
"Sian Long",
"Xi Luo",
"Hongbin Deng",
"Zhipeng He",
"Na Zhao",
"Yudong Luo",
"Sian Long",
"Xi Luo",
"Hongbin Deng"
] | Current multi-modal hybrid robots with flight and wheeled modes have fallen into the dilemma that they can only avoid obstacles by re-taking off when encountering obstacles due to the poor performance of wheeled obstacle-crossing. To tackle this problem, this paper presents a novel multi-modal hybrid robot with the ability to actively adjust the wheel’s size, which is inspired by the behavior of t... |
Topological Exploration using Segmented Map with Keyframe Contribution in Subterranean Environments | https://ieeexplore.ieee.org/document/10610605/ | [
"Boseong Kim",
"Hyunki Seong",
"D. Hyunchul Shim",
"Boseong Kim",
"Hyunki Seong",
"D. Hyunchul Shim"
] | Existing exploration algorithms mainly generate frontiers using random sampling or motion primitive methods within a specific sensor range or search space. However, frontiers generated within constrained spaces lead to back-and-forth maneuvers in large-scale environments, thereby diminishing exploration efficiency. To address this issue, we propose a method that utilizes a 3D dense map to generate... |
A Powerline Inspection UAV Equipped with Dexterous, Lockable Gripping Mechanisms for Autonomous Perching and Contact Rolling | https://ieeexplore.ieee.org/document/10610783/ | [
"Angus Lynch",
"Corey Duguid",
"Joao Buzzatto",
"Minas Liarokapis",
"Angus Lynch",
"Corey Duguid",
"Joao Buzzatto",
"Minas Liarokapis"
] | Inspection of powerlines is a hard problem that requires humans to operate in remote locations and dangerous conditions. This paper proposes a quadcopter unmanned aerial vehicle (UAV) equipped with rolling-capable perching mechanisms and a depth-vision system for the purpose of autonomous power line inspection. The perching mechanism grips onto the power line, allowing the UAV to withstand externa... |
GIRA: Gaussian Mixture Models for Inference and Robot Autonomy | https://ieeexplore.ieee.org/document/10611216/ | [
"Kshitij Goel",
"Wennie Tabib",
"Kshitij Goel",
"Wennie Tabib"
] | This paper introduces the open-source framework, GIRA, which implements fundamental robotics algorithms for reconstruction, pose estimation, and occupancy modeling using compact generative models. Compactness enables perception in the large by ensuring that the perceptual models can be communicated through low-bandwidth channels during large-scale mobile robot deployments. The generative property ... |
Seabed intervention with an underwater legged robot | https://ieeexplore.ieee.org/document/10611135/ | [
"Giacomo Picardi",
"Anna Astolfi",
"Marcello Calisti",
"Giacomo Picardi",
"Anna Astolfi",
"Marcello Calisti"
] | Efficiently performing intervention tasks underwater is crucial in various commercial and scientific sectors; however, propeller-driven vehicles face limitations due to their floating nature. In Remotely Operated Vehicles (ROVs) operations, this can be compensated by the ability of the operator, but they come with high operational costs. Instead, Autonomous Underwater Vehicles (AUVs) have shown pr... |
Predicting against the Flow: Boosting Source Localization by Means of Field Belief Modeling using Upstream Source Proximity | https://ieeexplore.ieee.org/document/10610144/ | [
"Finn L Busch",
"Nathalie Bauschmann",
"Sami Haddadin",
"Robert Seifried",
"Daniel A Duecker",
"Finn L Busch",
"Nathalie Bauschmann",
"Sami Haddadin",
"Robert Seifried",
"Daniel A Duecker"
] | Time-effective and accurate source localization with mobile robots is crucial in safety-critical scenarios, e.g. leakage detection. This becomes particular challenging in realistic cluttered scenarios, i.e. in the presence of complex current flows or wind. Traditional methods often fall short due to simplifications or limited onboard resources.We propose to combine source localization with a Gauss... |
A Turning Radius Prediction Scheme for Sailing Robots under Complex Marine Environment | https://ieeexplore.ieee.org/document/10611373/ | [
"Weimin Qi",
"Qinbo Sun",
"Huihuan Qian",
"Weimin Qi",
"Qinbo Sun",
"Huihuan Qian"
] | This paper presents a strategy for predicting the turning radius of a sailing robot with consideration of aerodynamic and hydrodynamic interferences from the marine environment. The turning radius is initially obtained based on three consecutive designated points during the turning process, which is regarded as the baseline method. Subsequently, on the basis of our constructed turning datasets, a ... |
WayIL: Image-based Indoor Localization with Wayfinding Maps | https://ieeexplore.ieee.org/document/10610480/ | [
"Obin Kwon",
"Dongki Jung",
"Youngji Kim",
"Soohyun Ryu",
"Suyong Yeon",
"Songhwai Oh",
"Donghwan Lee",
"Obin Kwon",
"Dongki Jung",
"Youngji Kim",
"Soohyun Ryu",
"Suyong Yeon",
"Songhwai Oh",
"Donghwan Lee"
] | This paper tackles a localization problem in large-scale indoor environments with wayfinding maps. A wayfinding map abstractly portrays the environment, and humans can localize themselves based on the map. However, when it comes to using it for robot localization, large geometrical discrepancies between the wayfinding map and the real world make it hard to use conventional localization methods. Ou... |
Globalizing Local Features: Image Retrieval Using Shared Local Features with Pose Estimation for Faster Visual Localization | https://ieeexplore.ieee.org/document/10610786/ | [
"Wenzheng Song",
"Ran Yan",
"Boshu Lei",
"Takayuki Okatani",
"Wenzheng Song",
"Ran Yan",
"Boshu Lei",
"Takayuki Okatani"
] | Visual localization is an important sub-task in SfM and visual SLAM that involves estimating a 6-DoF camera pose for an input query image relative to a given 3D model of the environment. The most accurate approach is a hierarchical one that splits the task into two stages: image retrieval and camera pose estimation. Each stage requires different image features, with global features compactly encod... |
Leveraging Neural Radiance Fields for Uncertainty-Aware Visual Localization | https://ieeexplore.ieee.org/document/10610126/ | [
"Le Chen",
"Weirong Chen",
"Rui Wang",
"Marc Pollefeys",
"Le Chen",
"Weirong Chen",
"Rui Wang",
"Marc Pollefeys"
] | As a promising fashion for visual localization, scene coordinate regression (SCR) has seen tremendous progress in the past decade. Most recent methods usually adopt neural networks to learn the mapping from image pixels to 3D scene coordinates, which requires a vast amount of annotated training data. We propose to leverage Neural Radiance Fields (NeRF) to generate training samples for SCR. Despite... |
OptiState: State Estimation of Legged Robots using Gated Networks with Transformer-based Vision and Kalman Filtering | https://ieeexplore.ieee.org/document/10610160/ | [
"Alexander Schperberg",
"Yusuke Tanaka",
"Saviz Mowlavi",
"Feng Xu",
"Bharathan Balaji",
"Dennis Hong",
"Alexander Schperberg",
"Yusuke Tanaka",
"Saviz Mowlavi",
"Feng Xu",
"Bharathan Balaji",
"Dennis Hong"
] | State estimation for legged robots is challenging due to their highly dynamic motion and limitations imposed by sensor accuracy. By integrating Kalman filtering, optimization, and learning-based modalities, we propose a hybrid solution that combines proprioception and exteroceptive information for estimating the state of the robot’s trunk. Leveraging joint encoder and IMU measurements, our Kalman ... |
ColonMapper: topological mapping and localization for colonoscopy | https://ieeexplore.ieee.org/document/10610426/ | [
"Javier Morlana",
"Juan D. Tardós",
"J. M. M. Montiel",
"Javier Morlana",
"Juan D. Tardós",
"J. M. M. Montiel"
] | We propose a topological mapping and localization system able to operate on real human colonoscopies, despite significant shape and illumination changes. The map is a graph where each node codes a colon location by a set of real images, while edges represent traversability between nodes. For close-in-time images, where scene changes are minor, place recognition can be successfully managed with the... |
Scene Action Maps: Behavioural Maps for Navigation without Metric Information | https://ieeexplore.ieee.org/document/10610489/ | [
"Joel Loo",
"David Hsu",
"Joel Loo",
"David Hsu"
] | Humans are remarkable in their ability to navigate without metric information. We can read abstract 2D maps, such as floor-plans or hand-drawn sketches, and use them to navigate in unseen rich 3D environments, without requiring prior traversals to map out these scenes in detail. We posit that this is enabled by the ability to represent the environment abstractly as interconnected navigational beha... |
Fast and Robust Normal Estimation for Sparse LiDAR Scans | https://ieeexplore.ieee.org/document/10611556/ | [
"Igor Bogoslavskyi",
"Konstantinos Zampogiannis",
"Raymond Phan",
"Igor Bogoslavskyi",
"Konstantinos Zampogiannis",
"Raymond Phan"
] | Light Detection and Ranging (LiDAR) technology has proven to be an important part of many robotics systems. Surface normals estimated from LiDAR data are commonly used for a variety of tasks in such systems. As most of the today’s mechanical LiDAR sensors produce sparse data, estimating normals from a single scan in a robust manner poses difficulties.In this paper, we address the problem of estima... |
OmniColor: A Global Camera Pose Optimization Approach of LiDAR-360Camera Fusion for Colorizing Point Clouds | https://ieeexplore.ieee.org/document/10610292/ | [
"Bonan Liu",
"Guoyang Zhao",
"Jianhao Jiao",
"Guang Cai",
"Chengyang Li",
"Handi Yin",
"Yuyang Wang",
"Ming Liu",
"Pan Hui",
"Bonan Liu",
"Guoyang Zhao",
"Jianhao Jiao",
"Guang Cai",
"Chengyang Li",
"Handi Yin",
"Yuyang Wang",
"Ming Liu",
"Pan Hui"
] | A Colored point cloud, as a simple and efficient 3D representation, has many advantages in various fields, including robotic navigation and scene reconstruction. This representation is now commonly used in 3D reconstruction tasks relying on cameras and LiDARs. However, fusing data from these two types of sensors is poorly performed in many existing frameworks, leading to unsatisfactory mapping res... |
InterRep: A Visual Interaction Representation for Robotic Grasping | https://ieeexplore.ieee.org/document/10610870/ | [
"Yu Cui",
"Qi Ye",
"Qingtao Liu",
"Anjun Chen",
"Gaofeng Li",
"Jiming Chen",
"Yu Cui",
"Qi Ye",
"Qingtao Liu",
"Anjun Chen",
"Gaofeng Li",
"Jiming Chen"
] | Recently, pre-trained vision models have gained significant attention in motor control, showcasing impressive performance across diverse robotic learning tasks. While previous works predominantly concentrate on the significance of the pre-training phase, the equally important task of extracting more effective representations based on existing pre-trained visual models remains unexplored. To better... |
Towards Feasible Dynamic Grasping: Leveraging Gaussian Process Distance Field, SE(3) Equivariance, and Riemannian Mixture Models | https://ieeexplore.ieee.org/document/10611601/ | [
"Ho Jin Choi",
"Nadia Figueroa",
"Ho Jin Choi",
"Nadia Figueroa"
] | This paper introduces a novel approach to improve robotic grasping in dynamic environments by integrating Gaussian Process Distance Fields (GPDF), SE(3) equivariant networks, and Riemannian Mixture Models. The aim is to enable robots to grasp moving objects effectively. Our approach comprises three main components: object shape reconstruction, grasp sampling, and implicit grasp pose selection. GPD... |
A Surprisingly Efficient Representation for Multi-Finger Grasping | https://ieeexplore.ieee.org/document/10611424/ | [
"Hengxu Yan",
"Hao-Shu Fang",
"Cewu Lu",
"Hengxu Yan",
"Hao-Shu Fang",
"Cewu Lu"
] | The problem of grasping objects using a multi-finger hand has received significant attention in recent years. However, it remains challenging to handle a large number of unfamiliar objects in real and cluttered environments. In this work, we propose a representation that can be effectively mapped to the multi-finger grasp space. Based on this representation, we develop a simple decision model that... |
GrainGrasp: Dexterous Grasp Generation with Fine-grained Contact Guidance | https://ieeexplore.ieee.org/document/10610035/ | [
"Fuqiang Zhao",
"Dzmitry Tsetserukou",
"Qian Liu",
"Fuqiang Zhao",
"Dzmitry Tsetserukou",
"Qian Liu"
] | One goal of dexterous robotic grasping is to allow robots to handle objects with the same level of flexibility and adaptability as humans. However, it remains a challenging task to generate an optimal grasping strategy for dexterous hands, especially when it comes to delicate manipulation and accurate adjustment the desired grasping poses for objects of varying shapes and sizes. In this paper, we ... |
Regrasping on Printed Circuit Boards with the Smart Suction Cup | https://ieeexplore.ieee.org/document/10610153/ | [
"Jungpyo Lee",
"Zheng Sun",
"Zhipeng Dong",
"Fei Chen",
"Hannah S. Stuart",
"Jungpyo Lee",
"Zheng Sun",
"Zhipeng Dong",
"Fei Chen",
"Hannah S. Stuart"
] | The disposal of waste electrical and electronic equipment (WEEE) presents a sustainability challenge, particularly for waste printed circuit boards (PCBs). PCBs are challenging to sort out from other waste materials in part because traditional industrial end-effectors struggle to reliably grip these irregularly shaped objects with unmodeled surface-mounted components. Vision-based separators, whil... |
Quasi-static Soft Fixture Analysis of Rigid and Deformable Objects | https://ieeexplore.ieee.org/document/10611593/ | [
"Yifei Dong",
"Florian T. Pokorny",
"Yifei Dong",
"Florian T. Pokorny"
] | We present a sampling-based approach to reasoning about the caging-based manipulation of rigid and a simplified class of deformable 3D objects subject to energy constraints. Towards this end, we propose the notion of soft fixtures extending earlier work on energy-bounded caging to include a broader set of energy function constraints, such as gravitational and elastic potential energy of 3D deforma... |
In-Hand Rolling Manipulation Based on Ball-on-Cloth System | https://ieeexplore.ieee.org/document/10609867/ | [
"Hinano Ichikura",
"Mitsuru Higashimori",
"Hinano Ichikura",
"Mitsuru Higashimori"
] | This paper presents a novel in-hand rolling manipulation method in which a ball on a cloth attached to fingertips is controlled using flexible and adaptive deformation of the cloth. First, an analytical model of the ball-on-cloth system is introduced. The shape of the cloth is simplified, and the rolling constraint of the ball on the cloth is defined focusing on the lowest point of the ball. Next,... |
Curriculum-based Sensing Reduction in Simulation to Real-World Transfer for In-hand Manipulation | https://ieeexplore.ieee.org/document/10610328/ | [
"Lingfeng Tao",
"Jiucai Zhang",
"Qiaojie Zheng",
"Xiaoli Zhang",
"Lingfeng Tao",
"Jiucai Zhang",
"Qiaojie Zheng",
"Xiaoli Zhang"
] | Simulation to Real-World Transfer allows affordable and fast training of learning-based robots for manipulation tasks using Deep Reinforcement Learning methods. Currently, Asymmetric Actor-Critic approaches are used for Sim2Real to reduce the rich idealized features in simulation to the accessible ones in the real world. However, the feature reduction from the simulation to the real world is condu... |
Geometric Fabrics: a Safe Guiding Medium for Policy Learning | https://ieeexplore.ieee.org/document/10610235/ | [
"Karl Van Wyk",
"Ankur Handa",
"Viktor Makoviychuk",
"Yijie Guo",
"Arthur Allshire",
"Nathan D. Ratliff",
"Karl Van Wyk",
"Ankur Handa",
"Viktor Makoviychuk",
"Yijie Guo",
"Arthur Allshire",
"Nathan D. Ratliff"
] | Robotics policies are always subjected to complex, second order dynamics that entangle their actions with resulting states. In reinforcement learning (RL) contexts, policies have the burden of deciphering these complicated interactions over massive amounts of experience and complex reward functions to learn how to accomplish tasks. Moreover, policies typically issue actions directly to controllers... |
Robust In-Hand Manipulation with Extrinsic Contacts | https://ieeexplore.ieee.org/document/10611664/ | [
"Boyuan Liang",
"Kei Ota",
"Masayoshi Tomizuka",
"Devesh K. Jha",
"Boyuan Liang",
"Kei Ota",
"Masayoshi Tomizuka",
"Devesh K. Jha"
] | We present in-hand manipulation tasks where a robot moves an object in grasp, maintains its external contact mode with the environment, and adjusts its in-hand pose simultaneously. The proposed manipulation task leads to complex contact interactions which can be very susceptible to uncertainties in kinematic and physical parameters. Therefore, we propose a robust in-hand manipulation method, which... |
Dexterous In-hand Manipulation by Guiding Exploration with Simple Sub-skill Controllers | https://ieeexplore.ieee.org/document/10611300/ | [
"Gagan Khandate",
"Cameron Paul Mehlman",
"Xingsheng Wei",
"Matei Ciocarlie",
"Gagan Khandate",
"Cameron Paul Mehlman",
"Xingsheng Wei",
"Matei Ciocarlie"
] | Recently, reinforcement learning has led to dexterous manipulation skills of increasing complexity. Nonetheless, learning these skills in simulation still exhibits poor sample-efficiency which stems from the fact these skills are learned from scratch without the benefit of any domain expertise. In this work, we aim to improve the sample efficiency of learning dexterous in-hand manipulation skills ... |
Robot Synesthesia: In-Hand Manipulation with Visuotactile Sensing | https://ieeexplore.ieee.org/document/10610532/ | [
"Ying Yuan",
"Haichuan Che",
"Yuzhe Qin",
"Binghao Huang",
"Zhao-Heng Yin",
"Kang-Won Lee",
"Yi Wu",
"Soo-Chul Lim",
"Xiaolong Wang",
"Ying Yuan",
"Haichuan Che",
"Yuzhe Qin",
"Binghao Huang",
"Zhao-Heng Yin",
"Kang-Won Lee",
"Yi Wu",
"Soo-Chul Lim",
"Xiaolong Wang"
] | Executing contact-rich manipulation tasks necessitates the fusion of tactile and visual feedback. However, the distinct nature of these modalities poses significant challenges. In this paper, we introduce a system that leverages visual and tactile sensory inputs to enable dexterous in-hand manipulation. Specifically, we propose Robot Synesthesia, a novel point cloudbased tactile representation ins... |
Robust 3D Object Detection from LiDAR-Radar Point Clouds via Cross-Modal Feature Augmentation | https://ieeexplore.ieee.org/document/10610775/ | [
"Jianning Deng",
"Gabriel Chan",
"Hantao Zhong",
"Chris Xiaoxuan Lu",
"Jianning Deng",
"Gabriel Chan",
"Hantao Zhong",
"Chris Xiaoxuan Lu"
] | This paper presents a novel framework for robust 3D object detection from point clouds via cross-modal hallucination. Our proposed approach is agnostic to either hallucination direction between LiDAR and 4D radar. We introduce multiple alignments on both spatial and feature levels to achieve simultaneous backbone refinement and hallucination generation. Specifically, spatial alignment is proposed ... |
LSSAttn: Towards Dense and Accurate View Transformation for Multi-modal 3D Object Detection | https://ieeexplore.ieee.org/document/10610830/ | [
"Qi Jiang",
"Hao Sun",
"Qi Jiang",
"Hao Sun"
] | Fusing the camera and LiDAR information in the unified BEV representation serves as the elegant paradigm for the 3D detection tasks. Current multi-modal fusion methods in BEV can be categorized into LSS-based and Transformer-based in terms of their view transformation. The former leverages inaccurate depth prediction and massive pseudo points for perspective-to-BEV transformation while the latter ... |
Learning Temporal Cues by Predicting Objects Move for Multi-camera 3D Object Detection | https://ieeexplore.ieee.org/document/10610934/ | [
"Seokha Moon",
"Hongbeen Park",
"Jaekoo Lee",
"Jinkyu Kim",
"Seokha Moon",
"Hongbeen Park",
"Jaekoo Lee",
"Jinkyu Kim"
] | In autonomous driving and robotics, there is a growing interest in utilizing short-term historical data to enhance multi-camera 3D object detection, leveraging the continuous and correlated nature of input video streams. Recent work has focused on spatially aligning BEV-based features over timesteps. However, this is often limited as its gain does not scale well with long-term past observations. T... |
HIC-YOLOv5: Improved YOLOv5 For Small Object Detection | https://ieeexplore.ieee.org/document/10610273/ | [
"Shiyi Tang",
"Shu Zhang",
"Yini Fang",
"Shiyi Tang",
"Shu Zhang",
"Yini Fang"
] | Small object detection has been a challenging problem in the field of object detection. There has been some works that proposes improvements for this task, such as adding several attention blocks or changing the whole structure of feature fusion networks. However, the computation cost of these models is large, which makes deploying a real-time object detection system unfeasible, while leaving room... |
CLIPUNetr: Assisting Human-robot Interface for Uncalibrated Visual Servoing Control with CLIP-driven Referring Expression Segmentation | https://ieeexplore.ieee.org/document/10611647/ | [
"Chen Jiang",
"Yuchen Yang",
"Martin Jagersand",
"Chen Jiang",
"Yuchen Yang",
"Martin Jagersand"
] | The classical human-robot interface in uncalibrated image-based visual servoing (UIBVS) relies on either human annotations or semantic segmentation with categorical labels. Both methods fail to match natural human communication and convey rich semantics in manipulation tasks as effectively as natural language expressions. In this paper, we tackle this problem by using referring expression segmenta... |
C2FDrone: Coarse-to-Fine Drone-to-Drone Detection using Vision Transformer Networks | https://ieeexplore.ieee.org/document/10609997/ | [
"Sairam VC Rebbapragada",
"Pranoy Panda",
"Vineeth N Balasubramanian",
"Sairam VC Rebbapragada",
"Pranoy Panda",
"Vineeth N Balasubramanian"
] | A vision-based drone-to-drone detection system is crucial for various applications like collision avoidance, countering hostile drones, and search-and-rescue operations. However, detecting drones presents unique challenges, including small object sizes, distortion, occlusion, and real-time processing requirements. Current methods integrating multi-scale feature fusion and temporal information have... |
Better Monocular 3D Detectors with LiDAR from the Past | https://ieeexplore.ieee.org/document/10610444/ | [
"Yurong You",
"Cheng Perng Phoo",
"Carlos Andres Diaz-Ruiz",
"Katie Z Luo",
"Wei-Lun Chao",
"Mark Campbell",
"Bharath Hariharan",
"Kilian Q Weinberger",
"Yurong You",
"Cheng Perng Phoo",
"Carlos Andres Diaz-Ruiz",
"Katie Z Luo",
"Wei-Lun Chao",
"Mark Campbell",
"Bharath Hariharan",
"Kilian Q Weinberger"
] | Accurate 3D object detection is crucial to autonomous driving. Though LiDAR-based detectors have achieved impressive performance, the high cost of LiDAR sensors precludes their widespread adoption in affordable vehicles. Camera-based detectors are cheaper alternatives but often suffer inferior performance compared to their LiDAR-based counterparts due to inherent depth ambiguities in images. In th... |
A Metacognitive Approach to Out-of-Distribution Detection for Segmentation | https://ieeexplore.ieee.org/document/10611287/ | [
"Meghna Gummadi",
"Cassandra Kent",
"Karl Schmeckpeper",
"Eric Eaton",
"Meghna Gummadi",
"Cassandra Kent",
"Karl Schmeckpeper",
"Eric Eaton"
] | Despite outstanding semantic scene segmentation in closed-worlds, deep neural networks segment novel instances poorly, which is required for autonomous agents acting in an open world. To improve out-of-distribution (OOD) detection for segmentation, we introduce a metacognitive approach in the form of a lightweight module that leverages entropy measures, segmentation predictions, and spatial contex... |
When to Replan? An Adaptive Replanning Strategy for Autonomous Navigation using Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/10611474/ | [
"Kohei Honda",
"Ryo Yonetani",
"Mai Nishimura",
"Tadashi Kozuno",
"Kohei Honda",
"Ryo Yonetani",
"Mai Nishimura",
"Tadashi Kozuno"
] | The hierarchy of global and local planners is one of the most commonly utilized system designs in autonomous robot navigation. While the global planner generates a reference path from the current to goal locations based on the pre-built map, the local planner produces a kinodynamic trajectory to follow the reference path while avoiding perceived obstacles. To account for unforeseen or dynamic obst... |
Resolving Loop Closure Confusion in Repetitive Environments for Visual SLAM through AI Foundation Models Assistance | https://ieeexplore.ieee.org/document/10610083/ | [
"Hongzhou Li",
"Sijie Yu",
"Shengkai Zhang",
"Guang Tan",
"Hongzhou Li",
"Sijie Yu",
"Shengkai Zhang",
"Guang Tan"
] | In visual SLAM (VSLAM) systems, loop closure plays a crucial role in reducing accumulated errors. However, VSLAM systems relying on low-level visual features often suffer from the problem of perceptual confusion in repetitive environments, where scenes in different locations are incorrectly identified as the same. Existing work has attempted to introduce object-level features or artificial landmar... |
Gen2Sim: Scaling up Robot Learning in Simulation with Generative Models | https://ieeexplore.ieee.org/document/10610566/ | [
"Pushkal Katara",
"Zhou Xian",
"Katerina Fragkiadaki",
"Pushkal Katara",
"Zhou Xian",
"Katerina Fragkiadaki"
] | Generalist robot manipulators need to learn a wide variety of manipulation skills across diverse environments. Current robot training pipelines rely on humans to provide kinesthetic demonstrations or to program simulation environments and to code up reward functions for reinforcement learning. Such human involvement is an important bottleneck towards scaling up robot learning across diverse tasks ... |
FLTRNN: Faithful Long-Horizon Task Planning for Robotics with Large Language Models | https://ieeexplore.ieee.org/document/10611663/ | [
"Jiatao Zhang",
"Lanling Tang",
"Yufan Song",
"Qiwei Meng",
"Haofu Qian",
"Jun Shao",
"Wei Song",
"Shiqiang Zhu",
"Jason Gu",
"Jiatao Zhang",
"Lanling Tang",
"Yufan Song",
"Qiwei Meng",
"Haofu Qian",
"Jun Shao",
"Wei Song",
"Shiqiang Zhu",
"Jason Gu"
] | Recent planning methods based on Large Language Models typically employ the In-Context Learning paradigm. Complex long-horizon planning tasks require more context(including instructions and demonstrations) to guarantee that the generated plan can be executed correctly. However, in such conditions, LLMs may overlook(unfaithful) the rules in the given context, resulting in the generated plans being ... |
Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models | https://ieeexplore.ieee.org/document/10611590/ | [
"Tsun-Hsuan Wang",
"Alaa Maalouf",
"Wei Xiao",
"Yutong Ban",
"Alexander Amini",
"Guy Rosman",
"Sertac Karaman",
"Daniela Rus",
"Tsun-Hsuan Wang",
"Alaa Maalouf",
"Wei Xiao",
"Yutong Ban",
"Alexander Amini",
"Guy Rosman",
"Sertac Karaman",
"Daniela Rus"
] | As autonomous driving technology matures, end-to-end methodologies have emerged as a leading strategy, promising seamless integration from perception to control via deep learning. However, existing systems grapple with challenges such as unexpected open set environments and the complexity of black-box models. At the same time, the evolution of deep learning introduces larger, multimodal foundation... |
AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers | https://ieeexplore.ieee.org/document/10611163/ | [
"Yongchao Chen",
"Jacob Arkin",
"Charles Dawson",
"Yang Zhang",
"Nicholas Roy",
"Chuchu Fan",
"Yongchao Chen",
"Jacob Arkin",
"Charles Dawson",
"Yang Zhang",
"Nicholas Roy",
"Chuchu Fan"
] | For effective human-robot interaction, robots need to understand, plan, and execute complex, long-horizon tasks described by natural language. Recent advances in large language models (LLMs) have shown promise for translating natural language into robot action sequences for complex tasks. However, existing approaches either translate the natural language directly into robot trajectories or factor ... |
Forgetting in Robotic Episodic Long-Term Memory | https://ieeexplore.ieee.org/document/10610299/ | [
"Joana Plewnia",
"Fabian Peller-Konrad",
"Tamim Asfour",
"Joana Plewnia",
"Fabian Peller-Konrad",
"Tamim Asfour"
] | Artificial cognitive architectures traditionally rely on complex memory models to encode, store, and retrieve information. However, the conventional practice of transferring all data from working memory (WM) to long-term memory (LTM) leads to high data volumes and challenges in efficient information processing and access. Deciding what information to retain or discard within a robot’s LTM is parti... |
Fixture calibration with guaranteed bounds from a few correspondence-free surface points | https://ieeexplore.ieee.org/document/10610632/ | [
"Rasmus Laurvig Haugaard",
"Yitaek Kim",
"Thorbjørn Mosekjær Iversen",
"Rasmus Laurvig Haugaard",
"Yitaek Kim",
"Thorbjørn Mosekjær Iversen"
] | Calibration of fixtures in robotic work cells is essential but also time consuming and error-prone, and poor calibration can easily lead to wasted debugging time in down-stream tasks. Contact-based calibration methods let the user measure points on the fixture’s surface with a tool tip attached to the robot’s end effector. Most such methods require the user to manually annotate correspondences on ... |
Towards fault-tolerant deployment of mobile robot navigation in the edge: an experimental study | https://ieeexplore.ieee.org/document/10611013/ | [
"Florian Mirus",
"Frederik Pasch",
"Kay-Ulrich Scholl",
"Florian Mirus",
"Frederik Pasch",
"Kay-Ulrich Scholl"
] | Modern algorithms allow robots to reach a greater level of autonomy and fulfill more challenging tasks. However, on-board limitations regarding computational and battery resources are hindering factors regarding the deployment of such algorithms particularly on mobile robots. Although offloading a majority of the algorithmic components to the edge or even cloud offers an attractive option to lever... |
Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs | https://ieeexplore.ieee.org/document/10611614/ | [
"Yiqun Duan",
"Qiang Zhang",
"Renjing Xu",
"Yiqun Duan",
"Qiang Zhang",
"Renjing Xu"
] | The utilization of Large Language Models (LLMs) within the realm of reinforcement learning, particularly as planners, has garnered a significant degree of attention in recent scholarly literature. However, a substantial proportion of existing research predominantly focuses on planning models for robotics that transmute the outputs derived from perception models into linguistic forms, thus adopting... |
DTPP: Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning in Autonomous Driving | https://ieeexplore.ieee.org/document/10610550/ | [
"Zhiyu Huang",
"Peter Karkus",
"Boris Ivanovic",
"Yuxiao Chen",
"Marco Pavone",
"Chen Lv",
"Zhiyu Huang",
"Peter Karkus",
"Boris Ivanovic",
"Yuxiao Chen",
"Marco Pavone",
"Chen Lv"
] | Motion prediction and cost evaluation are vital components in the decision-making system of autonomous vehicles. However, existing methods often ignore the importance of cost learning and treat them as separate modules. In this study, we employ a tree-structured policy planner and propose a differentiable joint training framework for both ego-conditioned prediction and cost models, resulting in a ... |
SIMMF: Semantics-aware Interactive Multiagent Motion Forecasting for Autonomous Vehicle Driving | https://ieeexplore.ieee.org/document/10611189/ | [
"Vidyaa Krishnan Nivash",
"Ahmed H. Qureshi",
"Vidyaa Krishnan Nivash",
"Ahmed H. Qureshi"
] | Autonomous vehicles require motion forecasting of their surrounding multiagents (pedestrians and vehicles) to make optimal decisions for navigation. The existing methods focus on techniques to utilize the positions and velocities of these agents and fail to capture semantic information from the scene. Moreover, to mitigate the increase in computational complexity associated with the number of agen... |
CausalAgents: A Robustness Benchmark for Motion Forecasting | https://ieeexplore.ieee.org/document/10610186/ | [
"Liting Sun",
"Rebecca Roelofs",
"Ben Caine",
"Khaled S. Refaat",
"Ben Sapp",
"Scott Ettinger",
"Wei Chai",
"Liting Sun",
"Rebecca Roelofs",
"Ben Caine",
"Khaled S. Refaat",
"Ben Sapp",
"Scott Ettinger",
"Wei Chai"
] | As machine learning models become increasingly prevalent in motion forecasting for autonomous vehicles (AVs), it is critical to ensure that model predictions are safe and reliable. In this paper, we examine the robustness of motion forecasting to non-causal perturbations. We construct a new benchmark for evaluating and improving model robustness by applying perturbations to existing data. Specific... |
Highway-Driving with Safe Velocity Bounds on Occluded Traffic | https://ieeexplore.ieee.org/document/10610904/ | [
"Truls Nyberg",
"Jonne van Haastregt",
"Jana Tumova",
"Truls Nyberg",
"Jonne van Haastregt",
"Jana Tumova"
] | Limited visibility and sensor occlusions pose pressing safety challenges for advanced driver-assistance systems (ADAS) and autonomous vehicles (AVs). In this work, our pursuit was to strike a balance: a method that ensures safety in occluded scenarios while preventing overly cautious behavior. We argue that such approaches are crucial for AVs’ future, particularly when navigating alongside human d... |
Generalizing Cooperative Eco-driving via Multi-residual Task Learning | https://ieeexplore.ieee.org/document/10610586/ | [
"Vindula Jayawardana",
"Sirui Li",
"Cathy Wu",
"Yashar Farid",
"Kentaro Oguchi",
"Vindula Jayawardana",
"Sirui Li",
"Cathy Wu",
"Yashar Farid",
"Kentaro Oguchi"
] | Conventional control, such as model-based control, is commonly utilized in autonomous driving due to its efficiency and reliability. However, real-world autonomous driving contends with a multitude of diverse traffic scenarios that are challenging for these planning algorithms. Model-free Deep Reinforcement Learning (DRL) presents a promising avenue in this direction, but learning DRL control poli... |
Approximate Multiagent Reinforcement Learning for On-Demand Urban Mobility Problem on a Large Map | https://ieeexplore.ieee.org/document/10611063/ | [
"Daniel Garces",
"Sushmita Bhattacharya",
"Dimitri Bertsekas",
"Stephanie Gil",
"Daniel Garces",
"Sushmita Bhattacharya",
"Dimitri Bertsekas",
"Stephanie Gil"
] | In this paper, we focus on the autonomous multiagent taxi routing problem for a large urban environment where the location and number of future ride requests are unknown a-priori, but can be estimated by an empirical distribution. Recent theory has shown that a rollout algorithm with a stable base policy produces a near-optimal stable policy. In the routing setting, a policy is stable if its execu... |
Continual Driving Policy Optimization with Closed-Loop Individualized Curricula | https://ieeexplore.ieee.org/document/10611578/ | [
"Haoyi Niu",
"Yizhou Xu",
"Xingjian Jiang",
"Jianming Hu",
"Haoyi Niu",
"Yizhou Xu",
"Xingjian Jiang",
"Jianming Hu"
] | The safety of autonomous vehicles (AV) has been a long-standing top concern, stemming from the absence of rare and safety-critical scenarios in the long-tail naturalistic driving distribution. To tackle this challenge, a surge of research in scenario-based autonomous driving has emerged, with a focus on generating high-risk driving scenarios and applying them to conduct safety-critical testing of ... |
Task-Driven Domain-Agnostic Learning with Information Bottleneck for Autonomous Steering | https://ieeexplore.ieee.org/document/10610479/ | [
"Yu Shen",
"Laura Zheng",
"Tianyi Zhou",
"Ming C. Lin",
"Yu Shen",
"Laura Zheng",
"Tianyi Zhou",
"Ming C. Lin"
] | Environments for autonomous driving can vary from place to place, leading to challenges in designing a learning model for a new scene. Transfer learning can leverage knowledge from a learned domain to a new domain with limited data. In this work, we focus on end-to-end autonomous driving as the target task, consisting of both perception and control. We first utilize information bottleneck analysis... |
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0 | https://ieeexplore.ieee.org/document/10611477/ | [
"Abby O’Neill",
"Abdul Rehman",
"Abhiram Maddukuri",
"Abhishek Gupta",
"Abhishek Padalkar",
"Abraham Lee",
"Acorn Pooley",
"Agrim Gupta",
"Ajay Mandlekar",
"Ajinkya Jain",
"Albert Tung",
"Alex Bewley",
"Alex Herzog",
"Alex Irpan",
"Alexander Khazatsky",
"Anant Rai",
"Anchit Gupta",
"Andrew Wang",
"Anikait Singh",
"Animesh Garg",
"Aniruddha Kembhavi",
"Annie Xie",
"Anthony Brohan",
"Antonin Raffin",
"Archit Sharma",
"Arefeh Yavary",
"Arhan Jain",
"Ashwin Balakrishna",
"Ayzaan Wahid",
"Ben Burgess-Limerick",
"Beomjoon Kim",
"Bernhard Schölkopf",
"Blake Wulfe",
"Brian Ichter",
"Cewu Lu",
"Charles Xu",
"Charlotte Le",
"Chelsea Finn",
"Chen Wang",
"Chenfeng Xu",
"Cheng Chi",
"Chenguang Huang",
"Christine Chan",
"Christopher Agia",
"Chuer Pan",
"Chuyuan Fu",
"Coline Devin",
"Danfei Xu",
"Daniel Morton",
"Danny Driess",
"Daphne Chen",
"Deepak Pathak",
"Dhruv Shah",
"Dieter Büchler",
"Dinesh Jayaraman",
"Dmitry Kalashnikov",
"Dorsa Sadigh",
"Edward Johns",
"Ethan Foster",
"Fangchen Liu",
"Federico Ceola",
"Fei Xia",
"Feiyu Zhao",
"Freek Stulp",
"Gaoyue Zhou",
"Gaurav S. Sukhatme",
"Gautam Salhotra",
"Ge Yan",
"Gilbert Feng",
"Giulio Schiavi",
"Glen Berseth",
"Gregory Kahn",
"Guanzhi Wang",
"Hao Su",
"Hao-Shu Fang",
"Haochen Shi",
"Henghui Bao",
"Heni Ben Amor",
"Henrik I Christensen",
"Hiroki Furuta",
"Homer Walke",
"Hongjie Fang",
"Huy Ha",
"Igor Mordatch",
"Ilija Radosavovic",
"Isabel Leal",
"Jacky Liang",
"Jad Abou-Chakra",
"Jaehyung Kim",
"Jaimyn Drake",
"Jan Peters",
"Jan Schneider",
"Jasmine Hsu",
"Jeannette Bohg",
"Jeffrey Bingham",
"Jeffrey Wu",
"Jensen Gao",
"Jiaheng Hu",
"Jiajun Wu",
"Jialin Wu",
"Jiankai Sun",
"Jianlan Luo",
"Jiayuan Gu",
"Jie Tan",
"Jihoon Oh",
"Jimmy Wu",
"Jingpei Lu",
"Jingyun Yang",
"Jitendra Malik",
"João Silvério",
"Joey Hejna",
"Jonathan Booher",
"Jonathan Tompson",
"Jonathan Yang",
"Jordi Salvador",
"Joseph J. Lim",
"Junhyek Han",
"Kaiyuan Wang",
"Kanishka Rao",
"Karl Pertsch",
"Karol Hausman",
"Keegan Go",
"Keerthana Gopalakrishnan",
"Ken Goldberg",
"Kendra Byrne",
"Kenneth Oslund",
"Kento Kawaharazuka",
"Kevin Black",
"Kevin Lin",
"Kevin Zhang",
"Kiana Ehsani",
"Kiran Lekkala",
"Kirsty Ellis",
"Krishan Rana",
"Krishnan Srinivasan",
"Kuan Fang",
"Kunal Pratap Singh",
"Kuo-Hao Zeng",
"Kyle Hatch",
"Kyle Hsu",
"Laurent Itti",
"Lawrence Yunliang Chen",
"Lerrel Pinto",
"Li Fei-Fei",
"Liam Tan",
"Linxi Jim Fan",
"Lionel Ott",
"Lisa Lee",
"Luca Weihs",
"Magnum Chen",
"Marion Lepert",
"Marius Memmel",
"Masayoshi Tomizuka",
"Masha Itkina",
"Mateo Guaman Castro",
"Max Spero",
"Maximilian Du",
"Michael Ahn",
"Michael C. Yip",
"Mingtong Zhang",
"Mingyu Ding",
"Minho Heo",
"Mohan Kumar Srirama",
"Mohit Sharma",
"Moo Jin Kim",
"Naoaki Kanazawa",
"Nicklas Hansen",
"Nicolas Heess",
"Nikhil J Joshi",
"Niko Suenderhauf",
"Ning Liu",
"Norman Di Palo",
"Nur Muhammad Mahi Shafiullah",
"Oier Mees",
"Oliver Kroemer",
"Osbert Bastani",
"Pannag R Sanketi",
"Patrick Tree Miller",
"Patrick Yin",
"Paul Wohlhart",
"Peng Xu",
"Peter David Fagan",
"Peter Mitrano",
"Pierre Sermanet",
"Pieter Abbeel",
"Priya Sundaresan",
"Qiuyu Chen",
"Quan Vuong",
"Rafael Rafailov",
"Ran Tian",
"Ria Doshi",
"Roberto Martín-Martín",
"Rohan Baijal",
"Rosario Scalise",
"Rose Hendrix",
"Roy Lin",
"Runjia Qian",
"Ruohan Zhang",
"Russell Mendonca",
"Rutav Shah",
"Ryan Hoque",
"Ryan Julian",
"Samuel Bustamante",
"Sean Kirmani",
"Sergey Levine",
"Shan Lin",
"Sherry Moore",
"Shikhar Bahl",
"Shivin Dass",
"Shubham Sonawani",
"Shuran Song",
"Sichun Xu",
"Siddhant Haldar",
"Siddharth Karamcheti",
"Simeon Adebola",
"Simon Guist",
"Soroush Nasiriany",
"Stefan Schaal",
"Stefan Welker",
"Stephen Tian",
"Subramanian Ramamoorthy",
"Sudeep Dasari",
"Suneel Belkhale",
"Sungjae Park",
"Suraj Nair",
"Suvir Mirchandani",
"Takayuki Osa",
"Tanmay Gupta",
"Tatsuya Harada",
"Tatsuya Matsushima",
"Ted Xiao",
"Thomas Kollar",
"Tianhe Yu",
"Tianli Ding",
"Todor Davchev",
"Tony Z. Zhao",
"Travis Armstrong",
"Trevor Darrell",
"Trinity Chung",
"Vidhi Jain",
"Vincent Vanhoucke",
"Wei Zhan",
"Wenxuan Zhou",
"Wolfram Burgard",
"Xi Chen",
"Xiaolong Wang",
"Xinghao Zhu",
"Xinyang Geng",
"Xiyuan Liu",
"Xu Liangwei",
"Xuanlin Li",
"Yao Lu",
"Yecheng Jason Ma",
"Yejin Kim",
"Yevgen Chebotar",
"Yifan Zhou",
"Yifeng Zhu",
"Yilin Wu",
"Ying Xu",
"Yixuan Wang",
"Yonatan Bisk",
"Yoonyoung Cho",
"Youngwoon Lee",
"Yuchen Cui",
"Yue Cao",
"Yueh-Hua Wu",
"Yujin Tang",
"Yuke Zhu",
"Yunchu Zhang",
"Yunfan Jiang",
"Yunshuang Li",
"Yunzhu Li",
"Yusuke Iwasawa",
"Yutaka Matsuo",
"Zehan Ma",
"Zhuo Xu",
"Zichen Jeff Cui",
"Zichen Zhang",
"Zipeng Lin",
"Abby O’Neill",
"Abdul Rehman",
"Abhiram Maddukuri",
"Abhishek Gupta",
"Abhishek Padalkar",
"Abraham Lee",
"Acorn Pooley",
"Agrim Gupta",
"Ajay Mandlekar",
"Ajinkya Jain",
"Albert Tung",
"Alex Bewley",
"Alex Herzog",
"Alex Irpan",
"Alexander Khazatsky",
"Anant Rai",
"Anchit Gupta",
"Andrew Wang",
"Anikait Singh",
"Animesh Garg",
"Aniruddha Kembhavi",
"Annie Xie",
"Anthony Brohan",
"Antonin Raffin",
"Archit Sharma",
"Arefeh Yavary",
"Arhan Jain",
"Ashwin Balakrishna",
"Ayzaan Wahid",
"Ben Burgess-Limerick",
"Beomjoon Kim",
"Bernhard Schölkopf",
"Blake Wulfe",
"Brian Ichter",
"Cewu Lu",
"Charles Xu",
"Charlotte Le",
"Chelsea Finn",
"Chen Wang",
"Chenfeng Xu",
"Cheng Chi",
"Chenguang Huang",
"Christine Chan",
"Christopher Agia",
"Chuer Pan",
"Chuyuan Fu",
"Coline Devin",
"Danfei Xu",
"Daniel Morton",
"Danny Driess",
"Daphne Chen",
"Deepak Pathak",
"Dhruv Shah",
"Dieter Büchler",
"Dinesh Jayaraman",
"Dmitry Kalashnikov",
"Dorsa Sadigh",
"Edward Johns",
"Ethan Foster",
"Fangchen Liu",
"Federico Ceola",
"Fei Xia",
"Feiyu Zhao",
"Freek Stulp",
"Gaoyue Zhou",
"Gaurav S. Sukhatme",
"Gautam Salhotra",
"Ge Yan",
"Gilbert Feng",
"Giulio Schiavi",
"Glen Berseth",
"Gregory Kahn",
"Guanzhi Wang",
"Hao Su",
"Hao-Shu Fang",
"Haochen Shi",
"Henghui Bao",
"Heni Ben Amor",
"Henrik I Christensen",
"Hiroki Furuta",
"Homer Walke",
"Hongjie Fang",
"Huy Ha",
"Igor Mordatch",
"Ilija Radosavovic",
"Isabel Leal",
"Jacky Liang",
"Jad Abou-Chakra",
"Jaehyung Kim",
"Jaimyn Drake",
"Jan Peters",
"Jan Schneider",
"Jasmine Hsu",
"Jeannette Bohg",
"Jeffrey Bingham",
"Jeffrey Wu",
"Jensen Gao",
"Jiaheng Hu",
"Jiajun Wu",
"Jialin Wu",
"Jiankai Sun",
"Jianlan Luo",
"Jiayuan Gu",
"Jie Tan",
"Jihoon Oh",
"Jimmy Wu",
"Jingpei Lu",
"Jingyun Yang",
"Jitendra Malik",
"João Silvério",
"Joey Hejna",
"Jonathan Booher",
"Jonathan Tompson",
"Jonathan Yang",
"Jordi Salvador",
"Joseph J. Lim",
"Junhyek Han",
"Kaiyuan Wang",
"Kanishka Rao",
"Karl Pertsch",
"Karol Hausman",
"Keegan Go",
"Keerthana Gopalakrishnan",
"Ken Goldberg",
"Kendra Byrne",
"Kenneth Oslund",
"Kento Kawaharazuka",
"Kevin Black",
"Kevin Lin",
"Kevin Zhang",
"Kiana Ehsani",
"Kiran Lekkala",
"Kirsty Ellis",
"Krishan Rana",
"Krishnan Srinivasan",
"Kuan Fang",
"Kunal Pratap Singh",
"Kuo-Hao Zeng",
"Kyle Hatch",
"Kyle Hsu",
"Laurent Itti",
"Lawrence Yunliang Chen",
"Lerrel Pinto",
"Li Fei-Fei",
"Liam Tan",
"Linxi Jim Fan",
"Lionel Ott",
"Lisa Lee",
"Luca Weihs",
"Magnum Chen",
"Marion Lepert",
"Marius Memmel",
"Masayoshi Tomizuka",
"Masha Itkina",
"Mateo Guaman Castro",
"Max Spero",
"Maximilian Du",
"Michael Ahn",
"Michael C. Yip",
"Mingtong Zhang",
"Mingyu Ding",
"Minho Heo",
"Mohan Kumar Srirama",
"Mohit Sharma",
"Moo Jin Kim",
"Naoaki Kanazawa",
"Nicklas Hansen",
"Nicolas Heess",
"Nikhil J Joshi",
"Niko Suenderhauf",
"Ning Liu",
"Norman Di Palo",
"Nur Muhammad Mahi Shafiullah",
"Oier Mees",
"Oliver Kroemer",
"Osbert Bastani",
"Pannag R Sanketi",
"Patrick Tree Miller",
"Patrick Yin",
"Paul Wohlhart",
"Peng Xu",
"Peter David Fagan",
"Peter Mitrano",
"Pierre Sermanet",
"Pieter Abbeel",
"Priya Sundaresan",
"Qiuyu Chen",
"Quan Vuong",
"Rafael Rafailov",
"Ran Tian",
"Ria Doshi",
"Roberto Martín-Martín",
"Rohan Baijal",
"Rosario Scalise",
"Rose Hendrix",
"Roy Lin",
"Runjia Qian",
"Ruohan Zhang",
"Russell Mendonca",
"Rutav Shah",
"Ryan Hoque",
"Ryan Julian",
"Samuel Bustamante",
"Sean Kirmani",
"Sergey Levine",
"Shan Lin",
"Sherry Moore",
"Shikhar Bahl",
"Shivin Dass",
"Shubham Sonawani",
"Shuran Song",
"Sichun Xu",
"Siddhant Haldar",
"Siddharth Karamcheti",
"Simeon Adebola",
"Simon Guist",
"Soroush Nasiriany",
"Stefan Schaal",
"Stefan Welker",
"Stephen Tian",
"Subramanian Ramamoorthy",
"Sudeep Dasari",
"Suneel Belkhale",
"Sungjae Park",
"Suraj Nair",
"Suvir Mirchandani",
"Takayuki Osa",
"Tanmay Gupta",
"Tatsuya Harada",
"Tatsuya Matsushima",
"Ted Xiao",
"Thomas Kollar",
"Tianhe Yu",
"Tianli Ding",
"Todor Davchev",
"Tony Z. Zhao",
"Travis Armstrong",
"Trevor Darrell",
"Trinity Chung",
"Vidhi Jain",
"Vincent Vanhoucke",
"Wei Zhan",
"Wenxuan Zhou",
"Wolfram Burgard",
"Xi Chen",
"Xiaolong Wang",
"Xinghao Zhu",
"Xinyang Geng",
"Xiyuan Liu",
"Xu Liangwei",
"Xuanlin Li",
"Yao Lu",
"Yecheng Jason Ma",
"Yejin Kim",
"Yevgen Chebotar",
"Yifan Zhou",
"Yifeng Zhu",
"Yilin Wu",
"Ying Xu",
"Yixuan Wang",
"Yonatan Bisk",
"Yoonyoung Cho",
"Youngwoon Lee",
"Yuchen Cui",
"Yue Cao",
"Yueh-Hua Wu",
"Yujin Tang",
"Yuke Zhu",
"Yunchu Zhang",
"Yunfan Jiang",
"Yunshuang Li",
"Yunzhu Li",
"Yusuke Iwasawa",
"Yutaka Matsuo",
"Zehan Ma",
"Zhuo Xu",
"Zichen Jeff Cui",
"Zichen Zhang",
"Zipeng Lin"
] | Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning method... |
Towards Generalizable Zero-Shot Manipulation via Translating Human Interaction Plans | https://ieeexplore.ieee.org/document/10610288/ | [
"Homanga Bharadhwaj",
"Abhinav Gupta",
"Vikash Kumar",
"Shubham Tulsiani",
"Homanga Bharadhwaj",
"Abhinav Gupta",
"Vikash Kumar",
"Shubham Tulsiani"
] | We pursue the goal of developing robots that can interact zero-shot with generic unseen objects via a diverse repertoire of manipulation skills and show how passive human videos can serve as a rich source of data for learning such generalist robots. Unlike typical robot learning approaches which directly learn how a robot should act from interaction data, we adopt a factorized approach that can le... |
Hearing Touch: Audio-Visual Pretraining for Contact-Rich Manipulation | https://ieeexplore.ieee.org/document/10611305/ | [
"Jared Mejia",
"Victoria Dean",
"Tess Hellebrekers",
"Abhinav Gupta",
"Jared Mejia",
"Victoria Dean",
"Tess Hellebrekers",
"Abhinav Gupta"
] | Although pre-training on a large amount of data is beneficial for robot learning, current paradigms only perform large-scale pretraining for visual representations, whereas representations for other modalities are trained from scratch. In contrast to the abundance of visual data, it is unclear what relevant internet-scale data may be used for pretraining other modalities such as tactile sensing. S... |
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention | https://ieeexplore.ieee.org/document/10611597/ | [
"Isabel Leal",
"Krzysztof Choromanski",
"Deepali Jain",
"Avinava Dubey",
"Jake Varley",
"Michael Ryoo",
"Yao Lu",
"Frederick Liu",
"Vikas Sindhwani",
"Quan Vuong",
"Tamas Sarlos",
"Ken Oslund",
"Karol Hausman",
"Kanishka Rao",
"Isabel Leal",
"Krzysztof Choromanski",
"Deepali Jain",
"Avinava Dubey",
"Jake Varley",
"Michael Ryoo",
"Yao Lu",
"Frederick Liu",
"Vikas Sindhwani",
"Quan Vuong",
"Tamas Sarlos",
"Ken Oslund",
"Karol Hausman",
"Kanishka Rao"
] | We present Self-Adaptive Robust Attention for Robotics Transformers (SARA-RT): a new paradigm for addressing the emerging challenge of scaling up Robotics Transformers (RT) for on-robot deployment. SARA-RT relies on the new method of fine-tuning proposed by us, called up-training. It converts pre-trained or already fine-tuned Transformer-based robotic policies of quadratic time complexity (includi... |
DenseTact-Mini: An Optical Tactile Sensor for Grasping Multi-Scale Objects From Flat Surfaces | https://ieeexplore.ieee.org/document/10610583/ | [
"Won Kyung Do",
"Ankush Kundan Dhawan",
"Mathilda Kitzmann",
"Monroe Kennedy",
"Won Kyung Do",
"Ankush Kundan Dhawan",
"Mathilda Kitzmann",
"Monroe Kennedy"
] | Dexterous manipulation, especially of small daily objects, continues to pose complex challenges in robotics. This paper introduces the DenseTact-Mini, an optical tactile sensor with a soft, rounded, smooth gel surface and compact design equipped with a synthetic fingernail. We propose three distinct grasping strategies: tap grasping using adhesion forces such as electrostatic and van der Waals, fi... |
Constrained Bimanual Planning with Analytic Inverse Kinematics | https://ieeexplore.ieee.org/document/10610675/ | [
"Thomas Cohn",
"Seiji Shaw",
"Max Simchowitz",
"Russ Tedrake",
"Thomas Cohn",
"Seiji Shaw",
"Max Simchowitz",
"Russ Tedrake"
] | In order for a bimanual robot to manipulate an object that is held by both hands, it must construct motion plans such that the transformation between its end effectors remains fixed. This amounts to complicated nonlinear equality constraints in the configuration space, which are difficult for trajectory optimizers. In addition, the set of feasible configurations becomes a measure zero set, which p... |
Deep Evidential Uncertainty Estimation for Semantic Segmentation under Out-Of-Distribution Obstacles | https://ieeexplore.ieee.org/document/10611342/ | [
"Siddharth Ancha",
"Philip R. Osteen",
"Nicholas Roy",
"Siddharth Ancha",
"Philip R. Osteen",
"Nicholas Roy"
] | In order to navigate safely and reliably in novel environments, robots must estimate perceptual uncertainty when confronted with out-of-distribution (OOD) obstacles not seen in training data. We present a method to accurately estimate pixel-wise uncertainty in semantic segmentation without requiring real or synthetic OOD examples at training time. From a shared per-pixel latent feature representat... |
NGEL-SLAM: Neural Implicit Representation-based Global Consistent Low-Latency SLAM System | https://ieeexplore.ieee.org/document/10611269/ | [
"Yunxuan Mao",
"Xuan Yu",
"Zhuqing Zhang",
"Kai Wang",
"Yue Wang",
"Rong Xiong",
"Yiyi Liao",
"Yunxuan Mao",
"Xuan Yu",
"Zhuqing Zhang",
"Kai Wang",
"Yue Wang",
"Rong Xiong",
"Yiyi Liao"
] | Neural implicit representations have emerged as a promising solution for providing dense geometry in Simultaneous Localization and Mapping (SLAM). However, existing methods in this direction fall short in terms of global consistency and low latency. This paper presents NGEL-SLAM to tackle the above challenges. To ensure global consistency, our system leverages a traditional feature-based tracking ... |
SeqTrack3D: Exploring Sequence Information for Robust 3D Point Cloud Tracking | https://ieeexplore.ieee.org/document/10611238/ | [
"Yu Lin",
"Zhiheng Li",
"Yubo Cui",
"Zheng Fang",
"Yu Lin",
"Zhiheng Li",
"Yubo Cui",
"Zheng Fang"
] | 3D single object tracking (SOT) is an important and challenging task for the autonomous driving and mobile robotics. Most existing methods perform tracking between two consecutive frames while ignoring the motion patterns of the target over a series of frames, which would cause performance degradation in the scenes with sparse points. To break through this limitation, we introduce "Sequence-to-Seq... |
Ultrafast Square-Root Filter-based VINS | https://ieeexplore.ieee.org/document/10610916/ | [
"Yuxiang Peng",
"Chuchu Chen",
"Guoquan Huang",
"Yuxiang Peng",
"Chuchu Chen",
"Guoquan Huang"
] | In this paper, we strongly advocate square-root covariance (instead of information) filtering for Visual-Inertial Navigation Systems (VINS), in particular on resource-constrained edge devices, because of its superior efficiency and numerical stability. Although VINS have made tremendous progress in recent years, they still face resource stringency and numerical instability on embedded systems when... |
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy | https://ieeexplore.ieee.org/document/10611125/ | [
"Zichen Zhang",
"Yunshuang Li",
"Osbert Bastani",
"Abhishek Gupta",
"Dinesh Jayaraman",
"Yecheng Jason Ma",
"Luca Weihs",
"Zichen Zhang",
"Yunshuang Li",
"Osbert Bastani",
"Abhishek Gupta",
"Dinesh Jayaraman",
"Yecheng Jason Ma",
"Luca Weihs"
] | Real-world robotic tasks stretch over extended horizons and encompass multiple stages. Learning long-horizon manipulation tasks, however, is a long-standing challenge, and demands decomposing the overarching task into several manageable subtasks to facilitate policy learning and generalization to unseen tasks. Prior task decomposition methods require task-specific knowledge, are computationally in... |
HEGN: Hierarchical Equivariant Graph Neural Network for 9DoF Point Cloud Registration | https://ieeexplore.ieee.org/document/10610562/ | [
"Adam Misik",
"Driton Salihu",
"Xin Su",
"Heike Brock",
"Eckehard Steinbach",
"Adam Misik",
"Driton Salihu",
"Xin Su",
"Heike Brock",
"Eckehard Steinbach"
] | Given its wide application in robotics, point cloud registration is a widely researched topic. Conventional methods aim to find a rotation and translation that align two point clouds in 6 degrees of freedom (DoF). However, certain tasks in robotics, such as category-level pose estimation, involve non-uniformly scaled point clouds, requiring a 9DoF transform for accurate alignment. We propose HEGN,... |
Multi-query TDSP for Path Planning in Time-varying Flow Fields | https://ieeexplore.ieee.org/document/10611501/ | [
"James Ju Heon Lee",
"Chanyeol Yoo",
"Stuart Anstee",
"Robert Fitch",
"James Ju Heon Lee",
"Chanyeol Yoo",
"Stuart Anstee",
"Robert Fitch"
] | Many applications of path planning in time-varying flow fields, particularly in areas such as marine robotics and ship routing, can be modelled as instances of the time-varying shortest path (TDSP) problem. Although there are no known polynomial-time solutions to TDSP in general, our recent work has identified a tractable case where the flow is modelled as piecewise constant. Extending this method... |
Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles | https://ieeexplore.ieee.org/document/10611021/ | [
"Kohei Honda",
"Naoki Akai",
"Kosuke Suzuki",
"Mizuho Aoki",
"Hirotaka Hosogaya",
"Hiroyuki Okuda",
"Tatsuya Suzuki",
"Kohei Honda",
"Naoki Akai",
"Kosuke Suzuki",
"Mizuho Aoki",
"Hirotaka Hosogaya",
"Hiroyuki Okuda",
"Tatsuya Suzuki"
] | This paper presents a novel Stochastic Optimal Control (SOC) method based on Model Predictive Path Integral control (MPPI), named Stein Variational Guided MPPI (SVG-MPPI), designed to handle rapidly shifting multimodal optimal action distributions. While MPPI can find a Gaussian-approximated optimal action distribution in closed form, i.e., without iterative solution updates, it struggles with the... |
An Efficient Solution to the 2D Visibility Problem in Cartesian Grid Maps and its Application in Heuristic Path Planning | https://ieeexplore.ieee.org/document/10611529/ | [
"Ibrahim Ibrahim",
"Joris Gillis",
"Wilm Decré",
"Jan Swevers",
"Ibrahim Ibrahim",
"Joris Gillis",
"Wilm Decré",
"Jan Swevers"
] | This paper introduces a novel, lightweight method to solve the visibility problem for 2D grids. The proposed method evaluates the existence of lines-of-sight from a source point to all other grid cells in a single pass with no preprocessing and independently of the number and shape of obstacles. It has a compute and memory complexity of $\mathcal{O}(n)$, where n = nx ×ny is the size of the grid, a... |
Efficient Clothoid Tree-Based Local Path Planning for Self-Driving Robots | https://ieeexplore.ieee.org/document/10610306/ | [
"Minhyeong Lee",
"Dongjun Lee",
"Minhyeong Lee",
"Dongjun Lee"
] | In this paper, we propose a real-time clothoid tree-based path planning for self-driving robots. Clothoids, curves that exhibit linear curvature profiles, play an important role in road design and path planning due to their appealing properties. Nevertheless, their real-time applications face considerable challenges, primarily stemming from the lack of a closed-form clothoid expression. To address... |
Decentralized Lifelong Path Planning for Multiple Ackerman Car-Like Robots | https://ieeexplore.ieee.org/document/10610330/ | [
"Teng Guo",
"Jingjin Yu",
"Teng Guo",
"Jingjin Yu"
] | Path planning for multiple non-holonomic robots in continuous domains constitutes a difficult robotics challenge with many applications. Despite significant recent progress on the topic, computationally efficient and high-quality solutions are lacking, especially in lifelong settings where robots must continuously take on new tasks. In this work, we make it possible to extend key ideas enabling st... |
Energy-Aware Ergodic Search: Continuous Exploration for Multi-Agent Systems with Battery Constraints | https://ieeexplore.ieee.org/document/10609871/ | [
"Adam Seewald",
"Cameron J. Lerch",
"Marvin Chancán",
"Aaron M. Dollar",
"Ian Abraham",
"Adam Seewald",
"Cameron J. Lerch",
"Marvin Chancán",
"Aaron M. Dollar",
"Ian Abraham"
] | Continuous exploration without interruption is important in scenarios such as search and rescue and precision agriculture, where consistent presence is needed to detect events over large areas. Ergodic search already derives continuous trajectories in these scenarios so that a robot spends more time in areas with high information density. However, existing literature on ergodic search does not con... |
Development of Variable Transmission Series Elastic Actuator for Hip Exoskeletons | https://ieeexplore.ieee.org/document/10611435/ | [
"Tianci Wang",
"Hao Wen",
"Zaixin Song",
"Zhiping Dong",
"Chunhua Liu",
"Tianci Wang",
"Hao Wen",
"Zaixin Song",
"Zhiping Dong",
"Chunhua Liu"
] | Series Elastic Actuator-based exoskeleton can offer precise torque control and transparency when interacting with human wearers. Accurate control of SEA-produced torques ensures the wearer’s voluntary motion and supports the implementation of multiple assistive paradigms. In this paper, a novel variable transmission series elastic actuator (VTSEA) is developed to meet torque-speed requirements in ... |
A Novel Compact Design of a Lever-Cam based Variable Stiffness Actuator: LC-VSA | https://ieeexplore.ieee.org/document/10610124/ | [
"Hongxi Zhu",
"Ulrike Thomas",
"Hongxi Zhu",
"Ulrike Thomas"
] | Ensuring safe interaction between humans and robots is an important challenge in robotics. In recent years, researchers have developed many different soft robots. One possibility to reach this goal is to integrate mechanical springs into their joints. The forthcoming generation of soft robots will be adaptable for joint stiffness to accommodate various tasks. Consequently, the development of varia... |
Design and Modeling of A Compact Serial Variable Stiffness Actuator (SVSA-III) with Linear Stiffness Profile | https://ieeexplore.ieee.org/document/10610331/ | [
"Shuowen Yi",
"Siyu Liu",
"Junbei Liao",
"Zhao Guo",
"Shuowen Yi",
"Siyu Liu",
"Junbei Liao",
"Zhao Guo"
] | Variable stiffness actuator (VSA) can imitate natural muscles in their compliance capbility, which can provide flexible adaptability for robots, improving the safety of robots interacting with the environment or human. This paper presents a new compact serial variable stiffness actuator ((SVSA-III)) with linear stiffness profile based on symmetrical variable lever arm mechanism. The stiffness moto... |
Experimental comparison of pinwheel and non-pinwheel designs of 3D-printed cycloidal gearing for robotics | https://ieeexplore.ieee.org/document/10610250/ | [
"Wesley Roozing",
"Glenn Roozing",
"Wesley Roozing",
"Glenn Roozing"
] | Recent trends in robotic actuation have highlighted the need for low cost, high performance, and efficient gearing. We present an experimental study comparing pinwheel and non-pinwheel designs of cycloidal gearing. The open source designs are 3D-printable, combined with off-the-shelf components, achieving a high performance-to-cost ratio. Extensive experimental data is presented, that compares two... |
A non-magnetic dual-mode linear pneumatic actuator: initial design and assessment | https://ieeexplore.ieee.org/document/10611707/ | [
"Timothée Portha",
"Laurent Barbé",
"François Geiskopf",
"Jonathan Vappou",
"Pierre Renaud",
"Timothée Portha",
"Laurent Barbé",
"François Geiskopf",
"Jonathan Vappou",
"Pierre Renaud"
] | A pneumatic linear actuator is presented and evaluated. Designed to operate in demanding environments such as MRI, it is developed to be used with two motion control modes: 1) a step-by-step mode with tooth-based gripping to ensure precision, 2) a continuous mode available locally for fine positioning. The actuator can also be disengaged to enable direct handling by an operator, for example for co... |
Accurate Kinematic Modeling using Autoencoders on Differentiable Joints | https://ieeexplore.ieee.org/document/10611062/ | [
"Nikolas Wilhelm",
"Sami Haddadin",
"Rainer Burgkart",
"Patrick Van Der Smagt",
"Maximilian Karl",
"Nikolas Wilhelm",
"Sami Haddadin",
"Rainer Burgkart",
"Patrick Van Der Smagt",
"Maximilian Karl"
] | In robotics and biomechanics, accurately determining joint parameters and computing the corresponding forward and inverse kinematics are critical yet often challenging tasks, especially when dealing with highly individualized and partly unknown systems. This paper unveils a cutting-edge kinematic optimizer, underpinned by an autoencoder-based architecture, to address these challenges. Utilizing a ... |
Jerk-limited Traversal of One-dimensional Paths and its Application to Multi-dimensional Path Tracking | https://ieeexplore.ieee.org/document/10611388/ | [
"Jonas C. Kiemel",
"Torsten Kröger",
"Jonas C. Kiemel",
"Torsten Kröger"
] | In this paper, we present an iterative method to quickly traverse multi-dimensional paths considering jerk constraints. As a first step, we analyze the traversal of each individual path dimension. We derive a range of feasible target accelerations for each intermediate waypoint of a one-dimensional path using a binary search algorithm. Computing a trajectory from waypoint to waypoint leads to the ... |
An Analytic Solution to the 3D CSC Dubins Path Problem | https://ieeexplore.ieee.org/document/10611360/ | [
"Victor M. Baez",
"Nikhil Navkar",
"Aaron T. Becker",
"Victor M. Baez",
"Nikhil Navkar",
"Aaron T. Becker"
] | We present an analytic solution to the 3D Dubins path problem for paths composed of an initial circular arc, a straight component, and a final circular arc. These are commonly called CSC paths. By modeling the start and goal configurations of the path as the base frame and final frame of an RRPRR manipulator, we treat this as an inverse kinematics problem. The kinematic features of the 3D Dubins p... |
Kinematic Optimization of a Robotic Arm for Automation Tasks with Human Demonstration | https://ieeexplore.ieee.org/document/10610924/ | [
"Inbar Meir",
"Avital Bechar",
"Avishai Sintov",
"Inbar Meir",
"Avital Bechar",
"Avishai Sintov"
] | Robotic arms are highly common in various automation processes such as manufacturing lines. However, these highly capable robots are usually degraded to simple repetitive tasks such as pick-and-place. On the other hand, designing an optimal robot for one specific task consumes large resources of engineering time and costs. In this paper, we propose a novel concept for optimizing the fitness of a r... |
Enhancing motion trajectory segmentation of rigid bodies using a novel screw-based trajectory-shape representation | https://ieeexplore.ieee.org/document/10610030/ | [
"Arno Verduyn",
"Maxim Vochten",
"Joris De Schutter",
"Arno Verduyn",
"Maxim Vochten",
"Joris De Schutter"
] | Trajectory segmentation refers to dividing a trajectory into meaningful consecutive sub-trajectories. This paper focuses on trajectory segmentation for 3D rigid-body motions. Most segmentation approaches in the literature represent the body’s trajectory as a point trajectory, considering only its translation and neglecting its rotation. We propose a novel trajectory representation for rigid-body m... |
Automatic Configuration of Multi-Agent Model Predictive Controllers based on Semantic Graph World Models | https://ieeexplore.ieee.org/document/10610708/ | [
"K. de Vos",
"E. Torta",
"H. Bruyninckx",
"C. A. López Martínez",
"M. J. G. van de Molengraft",
"K. de Vos",
"E. Torta",
"H. Bruyninckx",
"C. A. López Martínez",
"M. J. G. van de Molengraft"
] | We propose a shared semantic map architecture to construct and configure Model Predictive Controllers (MPC) dynamically, that solve navigation problems for multiple robotic agents sharing parts of the same environment. The navigation task is represented as a sequence of semantically labeled areas in the map, that must be traversed sequentially, i.e. a route. Each semantic label represents one or m... |
Meta-Reinforcement Learning Based Cooperative Surface Inspection of 3D Uncertain Structures using Multi-robot Systems | https://ieeexplore.ieee.org/document/10610420/ | [
"Junfeng Chen",
"Yuan Gao",
"Junjie Hu",
"Fuqin Deng",
"Tin Lun Lam",
"Junfeng Chen",
"Yuan Gao",
"Junjie Hu",
"Fuqin Deng",
"Tin Lun Lam"
] | This paper presents a decentralized cooperative motion planning approach for surface inspection of 3D structures which includes uncertainties like size, number, shape, position, using multi-robot systems (MRS). Given that most of existing works mainly focus on surface inspection of single and fully known 3D structures, our motivation is two-fold: first, 3D structures separately distributed in 3D e... |
Decentralized Multi-Agent Trajectory Planning in Dynamic Environments with Spatiotemporal Occupancy Grid Maps | https://ieeexplore.ieee.org/document/10610670/ | [
"Siyuan Wu",
"Gang Chen",
"Moji Shi",
"Javier Alonso-Mora",
"Siyuan Wu",
"Gang Chen",
"Moji Shi",
"Javier Alonso-Mora"
] | This paper proposes a decentralized trajectory planning framework for the collision avoidance problem of multiple micro aerial vehicles (MAVs) in environments with static and dynamic obstacles. The framework utilizes spatiotemporal occupancy grid maps (SOGM), which forecast the occupancy status of neighboring space in the near future, as the environment representation. Based on this representation... |
Communicating Intent as Behaviour Trees for Decentralised Multi-Robot Coordination | https://ieeexplore.ieee.org/document/10610441/ | [
"Rhett Hull",
"Diluka Moratuwage",
"Emily Scheide",
"Robert Fitch",
"Graeme Best",
"Rhett Hull",
"Diluka Moratuwage",
"Emily Scheide",
"Robert Fitch",
"Graeme Best"
] | We propose a decentralised multi-robot coordination algorithm that features a rich representation for encoding and communicating each robot’s intent. This representation for “intent messages” enables improved coordination behaviour and communication efficiency in difficult scenarios, such as those where there are unknown points of contention that require negotiation between robots. Each intent mes... |
Partial Belief Space Planning for Scaling Stochastic Dynamic Games | https://ieeexplore.ieee.org/document/10610219/ | [
"Kamran Vakil",
"Mela Coffey",
"Alyssa Pierson",
"Kamran Vakil",
"Mela Coffey",
"Alyssa Pierson"
] | This paper presents a method to reduce computations for stochastic dynamic games with game-theoretic belief space planning through partially propagating beliefs. Complex interactions in scenarios such as surveillance, herding, and racing can be modeled using game-theoretic frameworks in the belief space. Stochastic dynamic games can be solved to a local Nash Equilibrium using a game-theoretic beli... |
Decentralized Multi-Agent Active Search and Tracking when Targets Outnumber Agents | https://ieeexplore.ieee.org/document/10609977/ | [
"Arundhati Banerjee",
"Jeff Schneider",
"Arundhati Banerjee",
"Jeff Schneider"
] | Multi-agent multi-target tracking has a wide range of applications, including wildlife patrolling, security surveillance or environment monitoring. Such algorithms often make restrictive assumptions: the number of targets and/or their initial locations may be assumed known, or agents may be pre-assigned to monitor disjoint partitions of the environment, reducing the burden of exploration. This als... |
Multi-Robot Autonomous Exploration and Mapping Under Localization Uncertainty with Expectation-Maximization | https://ieeexplore.ieee.org/document/10611495/ | [
"Yewei Huang",
"Xi Lin",
"Brendan Englot",
"Yewei Huang",
"Xi Lin",
"Brendan Englot"
] | We propose an autonomous exploration algorithm designed for decentralized multi-robot teams, which takes into account map and localization uncertainties of range-sensing mobile robots. Virtual landmarks are used to quantify the combined impact of process noise and sensor noise on map uncertainty. Additionally, we employ an iterative expectation-maximization inspired algorithm to assess the potenti... |
Optimal Task Allocation for Heterogeneous Multi-robot Teams with Battery Constraints | https://ieeexplore.ieee.org/document/10611147/ | [
"Álvaro Calvo",
"Jesús Capitán",
"Álvaro Calvo",
"Jesús Capitán"
] | This paper presents a novel approach to optimal multi-robot task allocation in heterogeneous teams of robots. When robots have heterogeneous capabilities and there are diverse objectives and constraints to comply with, computing optimal plans can become especially hard. Moreover, we increase the problem complexity by: 1) considering battery-limited robots that need to schedule recharges; 2) tasks ... |
Bigraph Matching Weighted with Learnt Incentive Function for Multi-Robot Task Allocation | https://ieeexplore.ieee.org/document/10611094/ | [
"Steve Paul",
"Nathan Maurer",
"Souma Chowdhury",
"Steve Paul",
"Nathan Maurer",
"Souma Chowdhury"
] | Most real-world Multi-Robot Task Allocation (MRTA) problems require fast and efficient decision-making, which is often achieved using heuristics-aided methods such as genetic algorithms, auction-based methods, and bipartite graph matching methods. These methods often assume a form that lends better explainability compared to an end-to-end (learnt) neural network based policy for MRTA. However, der... |
Through the Real World Haze Scenes: Navigating the Synthetic-to-Real Gap in Challenging Image Dehazing | https://ieeexplore.ieee.org/document/10611709/ | [
"Shijie Chen",
"Mohammad Mahdizadeh",
"Chong Yu",
"Jiayuan Fan",
"Tao Chen",
"Shijie Chen",
"Mohammad Mahdizadeh",
"Chong Yu",
"Jiayuan Fan",
"Tao Chen"
] | Dehazing real-world hazy images is challenging due to the complexity of natural haze, varying haze conditions, details preservation, and the risk of overexposure. Existing methods excel in synthetic hazy scenarios but struggle in the real world because they don’t use all available features. Classical dehazing techniques primarily focus on low-level dehazing enhancements, whereas deep learning-base... |
CopperTag: A Real-Time Occlusion-Resilient Fiducial Marker | https://ieeexplore.ieee.org/document/10611260/ | [
"Xu Bian",
"Wenzhao Chen",
"Xiaoyu Tian",
"Donglai Ran",
"Xu Bian",
"Wenzhao Chen",
"Xiaoyu Tian",
"Donglai Ran"
] | Fiducial markers, like AprilTag and ArUco, are extensively utilized in robotics applications within industrial environments, encompassing navigation, docking, and object grasping tasks. However, in contrast to controlled laboratory conditions, markers installed in factory grounds or equipment surfaces, often face challenges like damage or contamination. These issues can lead to compromised marker ... |
Robust Collaborative Perception without External Localization and Clock Devices | https://ieeexplore.ieee.org/document/10610635/ | [
"Zixing Lei",
"Zhenyang Ni",
"Ruize Han",
"Shuo Tang",
"Chen Feng",
"Siheng Chen",
"Yanfeng Wang",
"Zixing Lei",
"Zhenyang Ni",
"Ruize Han",
"Shuo Tang",
"Chen Feng",
"Siheng Chen",
"Yanfeng Wang"
] | A consistent spatial-temporal coordination across multiple agents is fundamental for collaborative perception, which seeks to improve perception abilities through information exchange among agents. To achieve this spatial-temporal alignment, traditional methods depend on external devices to provide localization and clock signals. However, hardware-generated signals could be vulnerable to noise and... |
DerainNeRF: 3D Scene Estimation with Adhesive Waterdrop Removal | https://ieeexplore.ieee.org/document/10609981/ | [
"Yunhao Li",
"Jing Wu",
"Lingzhe Zhao",
"Peidong Liu",
"Yunhao Li",
"Jing Wu",
"Lingzhe Zhao",
"Peidong Liu"
] | When capturing images through the glass during rainy or snowy weather conditions, the resulting images often contain waterdrops adhered on the glass surface, and these waterdrops significantly degrade the image quality and performance of many computer vision algorithms. To tackle these limitations, we propose a method to reconstruct the clear 3D scene implicitly from multi-view images degraded by ... |
Marrying NeRF with Feature Matching for One-step Pose Estimation | https://ieeexplore.ieee.org/document/10610766/ | [
"Ronghan Chen",
"Yang Cong",
"Yu Ren",
"Ronghan Chen",
"Yang Cong",
"Yu Ren"
] | Given the image collection of an object, we aim at building a real-time image-based pose estimation method, which requires neither its CAD model nor hours of object-specific training. Recent NeRF-based methods provide a promising solution by directly optimizing the pose from pixel loss between rendered and target images. However, during inference, they require long converging time, and suffer from... |
Occluded Part-aware Graph Convolutional Networks for Skeleton-based Action Recognition | https://ieeexplore.ieee.org/document/10610972/ | [
"Min Hyuk Kim",
"Min Ju Kim",
"Seok Bong Yoo",
"Min Hyuk Kim",
"Min Ju Kim",
"Seok Bong Yoo"
] | Recognizing human action is one of the most critical factors in the visual perception of robots. Specifically, skeletonbased action recognition has been actively researched to enhance recognition performance at a lower cost. However, action recognition in occlusion situations, where body parts are not visible, is still challenging.We propose an occluded part-aware graph convolutional network (OP-G... |
MAL: Motion-Aware Loss with Temporal and Distillation Hints for Self-Supervised Depth Estimation | https://ieeexplore.ieee.org/document/10610688/ | [
"Yue-Jiang Dong",
"Fang-Lue Zhang",
"Song-Hai Zhang",
"Yue-Jiang Dong",
"Fang-Lue Zhang",
"Song-Hai Zhang"
] | Depth perception is crucial for a wide range of robotic applications. Multi-frame self-supervised depth estimation methods have gained research interest due to their ability to leverage large-scale, unlabeled real-world data. However, the self-supervised methods often rely on the assumption of a static scene and their performance tends to degrade in dynamic environments. To address this issue, we ... |
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