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Fast-MbyM: Leveraging Translational Invariance of the Fourier Transform for Efficient and Accurate Radar Odometry | https://ieeexplore.ieee.org/document/9812063/ | [
"Rob Weston",
"Matthew Gadd",
"Daniele De Martini",
"Paul Newman",
"Ingmar Posner",
"Rob Weston",
"Matthew Gadd",
"Daniele De Martini",
"Paul Newman",
"Ingmar Posner"
] | Masking by Moving (MByM), provides robust and accurate radar odometry measurements through an exhaustive correlative search across discretised pose candidates. However, this dense search creates a significant computational bottleneck which hinders real-time performance when high-end GPUs are not available. Utilising the translational invariance of the Fourier Transform, in our approach, Fast Maski... |
DA-LMR: A Robust Lane Marking Representation for Data Association | https://ieeexplore.ieee.org/document/9812271/ | [
"Miguel Ángel Muñoz-Bañón",
"Jan-Hendrik Pauls",
"Haohao Hu",
"Christoph Stiller",
"Miguel Ángel Muñoz-Bañón",
"Jan-Hendrik Pauls",
"Haohao Hu",
"Christoph Stiller"
] | While complete localization approaches are widely studied in the literature, their data association and data representation subprocesses usually go unnoticed. However, both are a key part of the final pose estimation. In this work, we present DA-LMR (Delta-Angle Lane Marking Representation), a robust data representation in the context of localization approaches. We propose a representation of lane... |
Neural Implicit Event Generator for Motion Tracking | https://ieeexplore.ieee.org/document/9812142/ | [
"Mana Masuda",
"Yusuke Sekikawa",
"Ryo Fujii",
"Hideo Saito",
"Mana Masuda",
"Yusuke Sekikawa",
"Ryo Fujii",
"Hideo Saito"
] | We present a novel framework of motion tracking from event data using implicit expression. Our framework uses pre-trained event generation MLP called the implicit event generator (IEG) and carries out motion tracking by updating its state (position and velocity) based on the difference between the observed event and generated event from the current state estimation. The difference is computed impl... |
Translation Invariant Global Estimation of Heading Angle Using Sinogram of LiDAR Point Cloud | https://ieeexplore.ieee.org/document/9811750/ | [
"Xiaqing Ding",
"Xuecheng Xu",
"Sha Lu",
"Yanmei Jiao",
"Mengwen Tan",
"Rong Xiong",
"Huanjun Deng",
"Mingyang Li",
"Yue Wang",
"Xiaqing Ding",
"Xuecheng Xu",
"Sha Lu",
"Yanmei Jiao",
"Mengwen Tan",
"Rong Xiong",
"Huanjun Deng",
"Mingyang Li",
"Yue Wang"
] | Global point cloud registration is an essential module for localization, of which the main difficulty exists in estimating the rotation globally without initial value. With the aid of gravity alignment, the degree of freedom in point cloud registration could be reduced to 4DoF, in which only the heading angle is required for rotation estimation. In this paper, we propose a fast and accurate global... |
LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition | https://ieeexplore.ieee.org/document/9811753/ | [
"Kavisha Vidanapathirana",
"Milad Ramezani",
"Peyman Moghadam",
"Sridha Sridharan",
"Clinton Fookes",
"Kavisha Vidanapathirana",
"Milad Ramezani",
"Peyman Moghadam",
"Sridha Sridharan",
"Clinton Fookes"
] | Retrieval-based place recognition is an efficient and effective solution for re-localization within a pre-built map, or global data association for Simultaneous Localization and Mapping (SLAM). The accuracy of such an approach is heavily dependant on the quality of the extracted scene-level representation. While end-to-end solutions - which learn a global descriptor from input point clouds - have ... |
AutoPlace: Robust Place Recognition with Single-chip Automotive Radar | https://ieeexplore.ieee.org/document/9811869/ | [
"Kaiwen Cai",
"Bing Wang",
"Chris Xiaoxuan Lu",
"Kaiwen Cai",
"Bing Wang",
"Chris Xiaoxuan Lu"
] | This paper presents a novel place recognition approach to autonomous vehicles by using low-cost, single-chip automotive radar. Aimed at improving recognition robustness and fully exploiting the rich information provided by this emerging automotive radar, our approach follows a principled pipeline that comprises (1) dynamic points removal from instant Doppler measurement, (2) spatial-temporal featu... |
GCLO: Ground Constrained LiDAR Odometry with Low-drifts for GPS-denied Indoor Environments | https://ieeexplore.ieee.org/document/9812336/ | [
"Xin Wei",
"Jixin Lv",
"Jie Sun",
"Erbao Dong",
"Shiliang Pu",
"Xin Wei",
"Jixin Lv",
"Jie Sun",
"Erbao Dong",
"Shiliang Pu"
] | LiDAR is widely adopted in Simultaneous Localization And Mapping (SLAM) and High Definition (HD) map production. The accuracy of LiDAR Odometry (LO) is of great importance, especially in GPS-denied environments. However, we found typical LO results are prone to drift upwards along the vertical direction in underground parking lots, leading to poor mapping results. This paper proposes a Ground Cons... |
ROW-SLAM: Under-Canopy Cornfield Semantic SLAM | https://ieeexplore.ieee.org/document/9811745/ | [
"Jiacheng Yuan",
"Jungseok Hong",
"Junaed Sattar",
"Volkan Isler",
"Jiacheng Yuan",
"Jungseok Hong",
"Junaed Sattar",
"Volkan Isler"
] | We study a semantic SLAM problem where a robot is tasked with autonomous weeding under the corn canopy. The goal is to detect corn stalks and localize them in a global coordinate frame. This is a challenging scenario for existing algorithms because there is very little space between the camera and the plants, and the camera motion is primarily restricted to be along the row. To overcome these chal... |
Loop Closure Detection and SLAM in Vineyards with Deep Semantic Cues | https://ieeexplore.ieee.org/document/9812419/ | [
"Alexios Papadimitriou",
"Ioannis Kleitsiotis",
"Ioannis Kostavelis",
"Ioannis Mariolis",
"Dimitrios Giakoumis",
"Spiriden Likothanassis",
"Dimitrios Tzovaras",
"Alexios Papadimitriou",
"Ioannis Kleitsiotis",
"Ioannis Kostavelis",
"Ioannis Mariolis",
"Dimitrios Giakoumis",
"Spiriden Likothanassis",
"Dimitrios Tzovaras"
] | Automation of vineyards cultivation necessitates for mobile robots to retain accurate localization system. The paper introduces a stereo vision-based Graph-Simultaneous Localization and Mapping (Graph-SLAM) pipeline custom-tailored to the specificities of vineyard fields. Graph-SLAM is reinforced with a Loop Closure Detection (LCD) based on semantic segmentation of the vine trees. The Mask R-CNN n... |
Precise 3D Reconstruction of Plants from UAV Imagery Combining Bundle Adjustment and Template Matching | https://ieeexplore.ieee.org/document/9811358/ | [
"Elias Marks",
"Federico Magistri",
"Cyrill Stachniss",
"Elias Marks",
"Federico Magistri",
"Cyrill Stachniss"
] | Monitoring individual plants and computing precise 3D reconstructions is highly relevant for crop breeding. In the conventional breeding approach, humans measure phenotypic traits by hand, requiring substantial manual labor. This paper addresses precise 3D plant reconstructions in a crop field or breeding plot based on UAV imagery. We explicitly address the challenges resulting from the thin struc... |
Self-supervised Representation Learning for Reliable Robotic Monitoring of Fruit Anomalies | https://ieeexplore.ieee.org/document/9811954/ | [
"Taeyeong Choi",
"Owen Would",
"Adrian Salazar-Gomez",
"Grzegorz Cielniak",
"Taeyeong Choi",
"Owen Would",
"Adrian Salazar-Gomez",
"Grzegorz Cielniak"
] | Data augmentation can be a simple yet powerful tool for autonomous robots to fully utilise available data for self-supervised identification of atypical scenes or objects. State-of-the-art augmentation methods arbitrarily embed “structural” peculiarity on typical images so that classifying these artefacts can provide guidance for learning representations for the detection of anomalous visual signa... |
Deep-CNN based Robotic Multi-Class Under-Canopy Weed Control in Precision Farming | https://ieeexplore.ieee.org/document/9812240/ | [
"Yayun Du",
"Guofeng Zhang",
"Darren Tsang",
"Mohammad Khalid Jawed",
"Yayun Du",
"Guofeng Zhang",
"Darren Tsang",
"Mohammad Khalid Jawed"
] | Smart weeding systems to perform plant-specific operations can contribute to the sustainability of agriculture and the environment. Despite monumental advances in autonomous robotic technologies for precision weed management in recent years, work on under-canopy weeding in fields is yet to be realized. A prerequisite of such systems is reliable detection and classification of weeds to avoid mistak... |
Precision fruit tree pruning using a learned hybrid vision/interaction controller | https://ieeexplore.ieee.org/document/9811628/ | [
"Alexander You",
"Hannah Kolano",
"Nidhi Parayil",
"Cindy Grimm",
"Joseph R. Davidson",
"Alexander You",
"Hannah Kolano",
"Nidhi Parayil",
"Cindy Grimm",
"Joseph R. Davidson"
] | Robotic tree pruning requires highly precise manipulator control in order to accurately align a cutting implement with the desired pruning point at the correct angle. Simultaneously, the robot must avoid applying excessive force to rigid parts of the environment such as trees, support posts, and wires. In this paper, we propose a hybrid control system that uses a learned vision-based controller to... |
Strawberry picking point localization ripeness and weight estimation | https://ieeexplore.ieee.org/document/9812303/ | [
"Alessandra Tafuro",
"Adeayo Adewumi",
"Soran Parsa",
"Ghalamzan E. Amir",
"Bappaditya Debnath",
"Alessandra Tafuro",
"Adeayo Adewumi",
"Soran Parsa",
"Ghalamzan E. Amir",
"Bappaditya Debnath"
] | Labour shortage, difficulties in labour management, the digitalization of fruit production pipeline to reduce the fruit production costs have made robotic systems for selective harvesting of strawberries an important industry and academic research. One of the important components of such technologies yet to be developed is fruit picking perception. For picking strawberries, a robot needs to infer ... |
Non-destructive Fruit Firmness Evaluation Using Vision-Based Tactile Information | https://ieeexplore.ieee.org/document/9811920/ | [
"Yaohui Chen",
"Jiahao Lin",
"Xuan Du",
"Bin Fang",
"Fuchun Sun",
"Shanjun Li",
"Yaohui Chen",
"Jiahao Lin",
"Xuan Du",
"Bin Fang",
"Fuchun Sun",
"Shanjun Li"
] | During postharvest storage, fruit firmness usually decreases due to respiration and bruise, the former of which indicates the fruit ripeness while the latter negatively influence consumers' taste preference. This paper presents a portable and low-cost device using vision-based tactile information to evaluate fruit firmness in a non-destructive manner. The device consists of a camera, LED lights, a... |
Deep Reinforcement Learning for Next-Best-View Planning in Agricultural Applications | https://ieeexplore.ieee.org/document/9811800/ | [
"Xiangyu Zeng",
"Tobias Zaenker",
"Maren Bennewitz",
"Xiangyu Zeng",
"Tobias Zaenker",
"Maren Bennewitz"
] | Automated agricultural applications, i.e., fruit picking require spatial information about crops and, especially, their fruits. In this paper, we present a novel deep reinforcement learning (DRL) approach to determine the next best view for automatic exploration of 3D environments with a robotic arm equipped with an RGB-D camera. We process the obtained images into an octree with labeled regions o... |
Mapping Unknown Environments With Instrumented Honey Bees | https://ieeexplore.ieee.org/document/9812399/ | [
"Haron Abdel-Raziq",
"Daniel Palmer",
"Alyosha Molnar",
"Kirstin Petersen",
"Haron Abdel-Raziq",
"Daniel Palmer",
"Alyosha Molnar",
"Kirstin Petersen"
] | Recent innovations in miniature sensors are driving a shift from robotic to bio-hybrid systems for exploration of unstructured environments. The ubiquity of honey bees in modern agriculture and ecology along with their superior agility, olfactory sense, and collective foraging skills make them a promising complement to traditional robots. This paper explores the potential of such systems based on ... |
Crossmodal Transformer Based Generative Framework for Pedestrian Trajectory Prediction | https://ieeexplore.ieee.org/document/9812226/ | [
"Zhaoxin Su",
"Gang Huang",
"Sanyuan Zhang",
"Wei Hua",
"Zhaoxin Su",
"Gang Huang",
"Sanyuan Zhang",
"Wei Hua"
] | Providing guidance about collision avoidance, pedestrian trajectory prediction is an important task for autonomous driving. In this paper, to produce plausible trajectory predictions in the first-person view circumstance, we propose a crossmodal transformer based generative framework which could leverage sequences of cues from multiple modalities as well as pedestrian attributes. For the encoder, ... |
Lightweight Monocular Depth Estimation through Guided Decoding | https://ieeexplore.ieee.org/document/9812220/ | [
"Michael Rudolph",
"Youssef Dawoud",
"Ronja Güldenring",
"Lazaros Nalpantidis",
"Vasileios Belagiannis",
"Michael Rudolph",
"Youssef Dawoud",
"Ronja Güldenring",
"Lazaros Nalpantidis",
"Vasileios Belagiannis"
] | We present a lightweight encoder-decoder architecture for monocular depth estimation, specifically designed for embedded platforms. Our main contribution is the Guided Upsampling Block (GUB) for building the decoder of our model. Motivated by the concept of guided image filtering, GUB relies on the image to guide the decoder on upsampling the feature representation and the depth map reconstruction... |
Propagating State Uncertainty Through Trajectory Forecasting | https://ieeexplore.ieee.org/document/9811776/ | [
"Boris Ivanovic",
"Yifeng Lin",
"Shubham Shrivastava",
"Punarjay Chakravarty",
"Marco Pavone",
"Boris Ivanovic",
"Yifeng Lin",
"Shubham Shrivastava",
"Punarjay Chakravarty",
"Marco Pavone"
] | Uncertainty pervades through the modern robotic autonomy stack, with nearly every component (e.g., sensors, detection, classification, tracking, behavior prediction) producing continuous or discrete probabilistic distributions. Trajectory forecasting, in particular, is surrounded by uncertainty as its inputs are produced by (noisy) upstream perception and its outputs are predictions that are often... |
De-snowing LiDAR Point Clouds With Intensity and Spatial-Temporal Features | https://ieeexplore.ieee.org/document/9812241/ | [
"Boyang Li",
"Jieling Li",
"Gang Chen",
"Hejun Wu",
"Kai Huang",
"Boyang Li",
"Jieling Li",
"Gang Chen",
"Hejun Wu",
"Kai Huang"
] | Point clouds from 3D light detection and ranging (LiDAR) are widely used. Noise caused by falling snow reduces the availability of point clouds. Due to the sparseness of LiDAR point clouds and the fact that the snow point clouds are easily affected by multi factors such as wind or snowfall conditions, it is difficult to accurately remove the snow while preserving the details of the point clouds. T... |
Refactoring ISP for High-Level Vision Tasks | https://ieeexplore.ieee.org/document/9812052/ | [
"Yongjie Shi",
"Songjiang Li",
"Xu Jia",
"Jianzhuang Liu",
"Yongjie Shi",
"Songjiang Li",
"Xu Jia",
"Jianzhuang Liu"
] | The image signal processing (ISP) pipeline, which transforms raw sensor measurement to a color image, is composed of a sequence of processing modules. Traditionally, the ISP pipeline is manually tuned by experts for human perception. The resulting handcrafted ISP configuration does not necessarily benefit the downstream high-level vision tasks. To mitigate these problems, this paper presents a sim... |
N-QGN: Navigation Map from a Monocular Camera using Quadtree Generating Networks | https://ieeexplore.ieee.org/document/9812362/ | [
"Daniel Braun",
"Olivier Morell",
"Pascal Vasseur",
"Cédric Demonceaux",
"Daniel Braun",
"Olivier Morell",
"Pascal Vasseur",
"Cédric Demonceaux"
] | Monocular depth estimation has been a popu-lar area of research for several years, especially since self-supervised networks have shown increasingly good results in bridging the gap with supervised and stereo methods. However, these approaches focus their interest on dense 3D reconstruction and sometimes on tiny details that are superfluous for autonomous navigation. In this paper, we propose to a... |
Depth-SIMS: Semi-Parametric Image and Depth Synthesis | https://ieeexplore.ieee.org/document/9811569/ | [
"Valentina Musat",
"Daniele De Martini",
"Matthew Gadd",
"Paul Newman",
"Valentina Musat",
"Daniele De Martini",
"Matthew Gadd",
"Paul Newman"
] | In this paper we present a compositing image synthesis method that generates RGB canvases with well aligned segmentation maps and sparse depth maps, coupled with an in-painting network that transforms the RGB canvases into high quality RGB images and the sparse depth maps into pixel-wise dense depth maps. We benchmark our method in terms of structural alignment and image quality, showing an increa... |
HoloSeg: An Efficient Holographic Segmentation Network for Real-time Scene Parsing | https://ieeexplore.ieee.org/document/9811930/ | [
"Shu Li",
"Qingqing Yan",
"Chengju Liu",
"Ming Liu",
"Qijun Chen",
"Shu Li",
"Qingqing Yan",
"Chengju Liu",
"Ming Liu",
"Qijun Chen"
] | Real-time semantic segmentation is a crucial but challenging dense prediction task for scene parsing. However, the existing CNN-based methods commonly bias the model in favor of speed-boosting compromising spatial resolution due to business requirements and hardware constrains, which impedes the high-accuracy segmentation result. To address the dilemma, we provide a novel Holographic Segmentation ... |
Lifting 2D Object Locations to 3D by Discounting LiDAR Outliers across Objects and Views | https://ieeexplore.ieee.org/document/9811693/ | [
"Robert McCraith",
"Eldar Insafutdinov",
"Lukas Neumann",
"Andrea Vedaldi",
"Robert McCraith",
"Eldar Insafutdinov",
"Lukas Neumann",
"Andrea Vedaldi"
] | We present a system for automatic converting of 2D mask object predictions and raw LiDAR point clouds into full 3D bounding boxes of objects. Because the LiDAR point clouds are partial, directly fitting bounding boxes to the point clouds is meaningless. Instead, we suggest that obtaining good results requires sharing information between all objects in the dataset jointly, over multiple frames. We ... |
VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles | https://ieeexplore.ieee.org/document/9812276/ | [
"Alexander Amini",
"Tsun-Hsuan Wang",
"Igor Gilitschenski",
"Wilko Schwarting",
"Zhijian Liu",
"Song Han",
"Sertac Karaman",
"Daniela Rus",
"Alexander Amini",
"Tsun-Hsuan Wang",
"Igor Gilitschenski",
"Wilko Schwarting",
"Zhijian Liu",
"Song Han",
"Sertac Karaman",
"Daniela Rus"
] | Simulation has the potential to transform the development of robust algorithms for mobile agents deployed in safety-critical scenarios. However, the poor photorealism and lack of diverse sensor modalities of existing simulation engines remain key hurdles towards realizing this potential. Here, we present VISTA††Full code release for the VISTA data-driven simulation engine is available here: vista.... |
Memory-based gaze prediction in deep imitation learning for robot manipulation | https://ieeexplore.ieee.org/document/9812087/ | [
"Heecheol Kim",
"Yoshiyuki Ohmura",
"Yasuo Kuniyoshi",
"Heecheol Kim",
"Yoshiyuki Ohmura",
"Yasuo Kuniyoshi"
] | Deep imitation learning is a promising approach that does not require hard-coded control rules in autonomous robot manipulation. The current applications of deep imitation learning to robot manipulation have been limited to reactive control based on the states at the current time step. However, future robots will also be required to solve tasks utilizing their memory obtained by experience in comp... |
Towards More Generalizable One-shot Visual Imitation Learning | https://ieeexplore.ieee.org/document/9812450/ | [
"Zhao Mandi",
"Fangchen Liu",
"Kimin Lee",
"Pieter Abbeel",
"Zhao Mandi",
"Fangchen Liu",
"Kimin Lee",
"Pieter Abbeel"
] | A general-purpose robot should be able to master a wide range of tasks and quickly learn a novel one by leveraging past experiences. One-shot imitation learning (OSIL) approaches this goal by training an agent with (pairs of) expert demonstrations, such that at test time, it can directly execute a new task from just one demonstration. However, so far this framework has been limited to training on ... |
Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation | https://ieeexplore.ieee.org/document/9811990/ | [
"Maximilian Igl",
"Daewoo Kim",
"Alex Kuefler",
"Paul Mougin",
"Punit Shah",
"Kyriacos Shiarlis",
"Dragomir Anguelov",
"Mark Palatucci",
"Brandyn White",
"Shimon Whiteson",
"Maximilian Igl",
"Daewoo Kim",
"Alex Kuefler",
"Paul Mougin",
"Punit Shah",
"Kyriacos Shiarlis",
"Dragomir Anguelov",
"Mark Palatucci",
"Brandyn White",
"Shimon Whiteson"
] | Simulation is a crucial tool for accelerating the development of autonomous vehicles. Making simulation realistic requires models of the human road users who interact with such cars. Such models can be obtained by applying learning from demonstration (LfD) to trajectories observed by cars already on the road. However, existing LfD methods are typically insufficient, yielding policies that frequent... |
Adversarial Imitation Learning from Video Using a State Observer | https://ieeexplore.ieee.org/document/9811570/ | [
"Haresh Karnan",
"Faraz Torabi",
"Garrett Warnell",
"Peter Stone",
"Haresh Karnan",
"Faraz Torabi",
"Garrett Warnell",
"Peter Stone"
] | The imitation learning research community has recently made significant progress towards the goal of enabling artificial agents to imitate behaviors from video demonstrations alone. However, current state-of-the-art approaches developed for this problem exhibit high sample complexity due, in part, to the high-dimensional nature of video observations. Towards addressing this issue, we introduce her... |
Modular Adaptive Policy Selection for Multi- Task Imitation Learning through Task Division | https://ieeexplore.ieee.org/document/9811819/ | [
"Dafni Antotsiou",
"Carlo Ciliberto",
"Tae–Kyun Kim",
"Dafni Antotsiou",
"Carlo Ciliberto",
"Tae–Kyun Kim"
] | Deep imitation learning requires many expert demonstrations, which can be hard to obtain, especially when many tasks are involved. However, different tasks often share similarities, so learning them jointly can greatly benefit them and alleviate the need for many demonstrations. But, joint multi-task learning often suffers from negative transfer, sharing information that should be task-specific. I... |
Disturbance-injected Robust Imitation Learning with Task Achievement | https://ieeexplore.ieee.org/document/9812376/ | [
"Hirotaka Tahara",
"Hikaru Sasaki",
"Hanbit Oh",
"Brendan Michael",
"Takamitsu Matsubara",
"Hirotaka Tahara",
"Hikaru Sasaki",
"Hanbit Oh",
"Brendan Michael",
"Takamitsu Matsubara"
] | Robust imitation learning using disturbance injections overcomes issues of limited variation in demonstrations. However, these methods assume demonstrations are optimal, and that policy stabilization can be learned via simple augmentations. In real-world scenarios, demonstrations are often of diverse-quality, and disturbance injection instead learns sub-optimal policies that fail to replicate desi... |
Learning Periodic Tasks from Human Demonstrations | https://ieeexplore.ieee.org/document/9812402/ | [
"Jingyun Yang",
"Junwu Zhang",
"Connor Settle",
"Akshara Rai",
"Rika Antonova",
"Jeannette Bohg",
"Jingyun Yang",
"Junwu Zhang",
"Connor Settle",
"Akshara Rai",
"Rika Antonova",
"Jeannette Bohg"
] | We develop a method for learning periodic tasks from visual demonstrations. The core idea is to leverage periodicity in the policy structure to model periodic aspects of the tasks. We use active learning to optimize parameters of rhythmic dynamic movement primitives (rDMPs) and propose an objective to maximize the similarity between the motion of objects manipulated by the robot and the desired mo... |
Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch | https://ieeexplore.ieee.org/document/9812127/ | [
"Eddy Hudson",
"Garrett Warnell",
"Faraz Torabi",
"Peter Stone",
"Eddy Hudson",
"Garrett Warnell",
"Faraz Torabi",
"Peter Stone"
] | Learning from demonstrations in the wild (e.g. YouTube videos) is a tantalizing goal in imitation learning. However, for this goal to be achieved, imitation learning algorithms must deal with the fact that the demonstrators and learners may have bodies that differ from one another. This condition — “embodiment mismatch” — is ignored by many recent imitation learning algorithms. Our proposed imitat... |
Multi-Task Learning with Sequence-Conditioned Transporter Networks | https://ieeexplore.ieee.org/document/9812096/ | [
"Michael H. Lim",
"Andy Zeng",
"Brian Ichter",
"Maryam Bandari",
"Erwin Coumans",
"Claire Tomlin",
"Stefan Schaal",
"Aleksandra Faust",
"Michael H. Lim",
"Andy Zeng",
"Brian Ichter",
"Maryam Bandari",
"Erwin Coumans",
"Claire Tomlin",
"Stefan Schaal",
"Aleksandra Faust"
] | Enabling robots to solve multiple manipulation tasks has a wide range of industrial applications. While learning-based approaches enjoy flexibility and generalizability, scaling these approaches to solve such compositional tasks remains a challenge. In this work, we aim to solve multi-task learning through the lens of sequence-conditioning and weighted sampling. First, we propose a new suite of be... |
VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation | https://ieeexplore.ieee.org/document/9812316/ | [
"Haresh Karnan",
"Garrett Warnell",
"Xuesu Xiao",
"Peter Stone",
"Haresh Karnan",
"Garrett Warnell",
"Xuesu Xiao",
"Peter Stone"
] | While imitation learning for vision-based au-tonomous mobile robot navigation has recently received a great deal of attention in the research community, existing approaches typically require state-action demonstrations that were gathered using the deployment platform. However, what if one cannot easily outfit their platform to record these demonstration signals or-worse yet-the demonstrator does n... |
Generalizable task representation learning from human demonstration videos: a geometric approach | https://ieeexplore.ieee.org/document/9812195/ | [
"Jun Jin",
"Martin Jagersand",
"Jun Jin",
"Martin Jagersand"
] | We study the problem of generalizable task learning from human demonstration videos without extra training on the robot or pre-recorded robot motions. Given a set of human demonstration videos showing a task with different objects/tools (categorical objects), we aim to learn a representation of visual observation that generalizes to categorical objects and enables efficient controller design. We p... |
Look and Listen: A Multi-Sensory Pouring Network and Dataset for Granular Media from Human Demonstrations | https://ieeexplore.ieee.org/document/9812125/ | [
"Alexis Burns",
"Siyuan Xiang",
"Daewon Lee",
"Larry Jackel",
"Shuran Song",
"Volkan Isler",
"Alexis Burns",
"Siyuan Xiang",
"Daewon Lee",
"Larry Jackel",
"Shuran Song",
"Volkan Isler"
] | Humans have the ability to pour various media, both liquid and granular, to desired ends in various containers. We do this by using multiple senses simultaneously in a constant feedback loop to complete a pouring task. Combining multiple sensing modalities, similar to humans, could aid in robotic pouring control outside of a structured or industrial setting. We present a multi-sensory pouring data... |
Predicting Like A Pilot: Dataset and Method to Predict Socially-Aware Aircraft Trajectories in Non-Towered Terminal Airspace | https://ieeexplore.ieee.org/document/9811972/ | [
"Jay Patrikar",
"Brady Moon",
"Jean Oh",
"Sebastian Scherer",
"Jay Patrikar",
"Brady Moon",
"Jean Oh",
"Sebastian Scherer"
] | Pilots operating aircraft in non-towered terminal airspace rely on their situational awareness and prior knowledge to predict the future trajectories of other agents. These predictions are conditioned on the past trajectories of other agents, agent-agent social interactions and environmental context such as airport location and weather. This paper provides a dataset, TrajAir, that captures this be... |
ORFD: A Dataset and Benchmark for Off-Road Freespace Detection | https://ieeexplore.ieee.org/document/9812139/ | [
"Chen Min",
"Weizhong Jiang",
"Dawei Zhao",
"Jiaolong Xu",
"Liang Xiao",
"Yiming Nie",
"Bin Dai",
"Chen Min",
"Weizhong Jiang",
"Dawei Zhao",
"Jiaolong Xu",
"Liang Xiao",
"Yiming Nie",
"Bin Dai"
] | Freespace detection is an essential component of autonomous driving technology and plays an important role in trajectory planning. In the last decade, deep learning based freespace detection methods have been proved feasible. However, these efforts were focused on urban road environments and few deep learning based methods were specifically designed for off-road freespace detection due to the lack... |
IPS300+: a Challenging multi-modal data sets for Intersection Perception System | https://ieeexplore.ieee.org/document/9811699/ | [
"Huanan Wang",
"Xinyu Zhang",
"Zhiwei Li",
"Jun Li",
"Kun Wang",
"Zhu Lei",
"Ren Haibing",
"Huanan Wang",
"Xinyu Zhang",
"Zhiwei Li",
"Jun Li",
"Kun Wang",
"Zhu Lei",
"Ren Haibing"
] | Due to high complexity and occlusion, insufficient perception in the crowded urban intersection can be a serious safety risk for both human drivers and autonomous algorithms, whereas CVIS (Cooperative Vehicle Infrastructure System) is a proposed solution for full-participants perception under this scenario. However, the research on roadside multi-modal perception is still in its infancy, and there... |
TartanDrive: A Large-Scale Dataset for Learning Off-Road Dynamics Models | https://ieeexplore.ieee.org/document/9811648/ | [
"Samuel Triest",
"Matthew Sivaprakasam",
"Sean J. Wang",
"Wenshan Wang",
"Aaron M. Johnson",
"Sebastian Scherer",
"Samuel Triest",
"Matthew Sivaprakasam",
"Sean J. Wang",
"Wenshan Wang",
"Aaron M. Johnson",
"Sebastian Scherer"
] | We present TartanDrive, a large scale dataset for learning dynamics models for off-road driving. We collected a dataset of roughly 200,000 off-road driving interactions on a modified Yamaha Viking ATV with seven unique sensing modalities in diverse terrains. To the authors' knowledge, this is the largest real-world multi-modal off-road driving dataset, both in terms of number of interactions and s... |
Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Items | https://ieeexplore.ieee.org/document/9811809/ | [
"Laura Downs",
"Anthony Francis",
"Nate Koenig",
"Brandon Kinman",
"Ryan Hickman",
"Krista Reymann",
"Thomas B. McHugh",
"Vincent Vanhoucke",
"Laura Downs",
"Anthony Francis",
"Nate Koenig",
"Brandon Kinman",
"Ryan Hickman",
"Krista Reymann",
"Thomas B. McHugh",
"Vincent Vanhoucke"
] | Interactive 3D simulations have enabled break-throughs in robotics and computer vision, but simulating the broad diversity of environments needed for deep learning requires large corpora of photo-realistic 3D object models. To address this need, we present Google Scanned Objects, an open-source collection of over one thousand 3D-scanned household items released under a Creative Commons license; th... |
Cityscapes TL++: Semantic Traffic Light Annotations for the Cityscapes Dataset | https://ieeexplore.ieee.org/document/9812144/ | [
"Johannes Janosovits",
"Johannes Janosovits"
] | There is a gap in holistic urban scene understanding between multi-modal datasets for segmentation and object detection on the one hand and traffic light datasets on the other hand. The role of traffic lights in the former is not labelled, making it difficult to use them for higher-level tasks and leave critical information of an intersection scene blank. Including traffic lights from traffic ligh... |
How to Build a Curb Dataset with LiDAR Data for Autonomous Driving | https://ieeexplore.ieee.org/document/9811676/ | [
"Dongfeng Bai",
"Tongtong Cao",
"Jingming Guo",
"Bingbing Liu",
"Dongfeng Bai",
"Tongtong Cao",
"Jingming Guo",
"Bingbing Liu"
] | Curbs are one of the essential elements of urban and highway traffic environments. Robust curb detection provides road structure information for motion planning in an autonomous driving system. Commonly, video cameras and 3D LiDARs are mounted on autonomous vehicles for curb detection. However, camera-based methods suffer from challenging illumination conditions. During the long period of time bef... |
OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication | https://ieeexplore.ieee.org/document/9812038/ | [
"Runsheng Xu",
"Hao Xiang",
"Xin Xia",
"Xu Han",
"Jinlong Li",
"Jiaqi Ma",
"Runsheng Xu",
"Hao Xiang",
"Xin Xia",
"Xu Han",
"Jinlong Li",
"Jiaqi Ma"
] | Employing Vehicle-to-Vehicle communication to enhance perception performance in self-driving technology has attracted considerable attention recently; however, the absence of a suitable open dataset for benchmarking algorithms has made it difficult to develop and assess cooperative perception technologies. To this end, we present the first large-scale open simulated dataset for Vehicle-to-Vehicle ... |
RF-Annotate: Automatic RF-Supervised Image Annotation of Common Objects in Context | https://ieeexplore.ieee.org/document/9812072/ | [
"Emerson Sie",
"Deepak Vasisht",
"Emerson Sie",
"Deepak Vasisht"
] | Wireless tags are increasingly used to track and identify common items of interest such as retail goods, food, medicine, clothing, books, documents, keys, equipment, and more. At the same time, there is a need for labelled visual data featuring such items for the purpose of training object detection and recognition models for robots operating in homes, warehouses, stores, libraries, pharmacies, an... |
Multi-modal Motion Prediction with Transformer-based Neural Network for Autonomous Driving | https://ieeexplore.ieee.org/document/9812060/ | [
"Zhiyu Huang",
"Xiaoyu Mo",
"Chen Lv",
"Zhiyu Huang",
"Xiaoyu Mo",
"Chen Lv"
] | Predicting the behaviors of other agents on the road is critical for autonomous driving to ensure safety and efficiency. However, the challenging part is how to represent the social interactions between agents and output different possible trajectories with interpretability. In this paper, we introduce a neural prediction framework based on the Transformer structure to model the relationship among... |
HiTPR: Hierarchical Transformer for Place Recognition in Point Cloud | https://ieeexplore.ieee.org/document/9811737/ | [
"Zhixing Hou",
"Yan Yan",
"Chengzhong Xu",
"Hui Kong",
"Zhixing Hou",
"Yan Yan",
"Chengzhong Xu",
"Hui Kong"
] | Place recognition or loop closure detection is one of the core components in a full SLAM system. In this paper, aiming at strengthening the relevancy of local neighboring points and the contextual dependency among global points simultaneously, we investigate the exploitation of transformer-based network for feature extraction, and propose a Hierarchical Transformer for Place Recognition (HiTPR). T... |
Diff-Net: Image Feature Difference Based High-Definition Map Change Detection for Autonomous Driving | https://ieeexplore.ieee.org/document/9811573/ | [
"Lei He",
"Shengjie Jiang",
"Xiaoqing Liang",
"Ning Wang",
"Shiyu Song",
"Lei He",
"Shengjie Jiang",
"Xiaoqing Liang",
"Ning Wang",
"Shiyu Song"
] | Up-to-date High-Definition (HD) maps are essential for self-driving cars. To achieve constantly updated HD maps, we present a deep neural network (DNN), Diff-Net, to detect changes in them. Compared to traditional methods based on object detectors, the essential design in our work is a parallel feature difference calculation structure that infers map changes by comparing features extracted from th... |
Context is Everything: Implicit Identification for Dynamics Adaptation | https://ieeexplore.ieee.org/document/9812119/ | [
"Ben Evans",
"Abitha Thankaraj",
"Lerrel Pinto",
"Ben Evans",
"Abitha Thankaraj",
"Lerrel Pinto"
] | Understanding environment dynamics is necessary for robots to act safely and optimally in the world. In realistic scenarios, dynamics are non-stationary and the causal variables such as environment parameters cannot necessarily be precisely measured or inferred, even during training. We propose Implicit Identification for Dynamics Adaptation (IIDA), a simple method to allow predictive models to ad... |
Unsupervised Domain Adaptation in LiDAR Semantic Segmentation with Self-Supervision and Gated Adapters | https://ieeexplore.ieee.org/document/9811654/ | [
"Mrigank Rochan",
"Shubhra Aich",
"Eduardo R. Corral-Soto",
"Amir Nabatchian",
"Bingbing Liu",
"Mrigank Rochan",
"Shubhra Aich",
"Eduardo R. Corral-Soto",
"Amir Nabatchian",
"Bingbing Liu"
] | In this paper, we focus on a less explored, but more realistic and complex problem of domain adaptation in LiDAR semantic segmentation. There is a significant drop in performance of an existing segmentation model when training (source domain) and testing (target domain) data originate from different LiDAR sensors. To overcome this shortcoming, we propose an unsupervised domain adaptation framework... |
Implicit Kinematic Policies: Unifying Joint and Cartesian Action Spaces in End-to-End Robot Learning | https://ieeexplore.ieee.org/document/9812165/ | [
"Aditya Ganapathi",
"Pete Florence",
"Jake Varley",
"Kaylee Burns",
"Ken Goldberg",
"Andy Zeng",
"Aditya Ganapathi",
"Pete Florence",
"Jake Varley",
"Kaylee Burns",
"Ken Goldberg",
"Andy Zeng"
] | Action representation is an important yet often overlooked aspect in end-to-end robot learning with deep networks. Choosing one action space over another (e.g. target joint positions, or Cartesian end-effector poses) can result in surprisingly stark performance differences between various downstream tasks - and as a result, considerable research has been devoted to finding the right action space f... |
SEMI: Self-supervised Exploration via Multisensory Incongruity | https://ieeexplore.ieee.org/document/9811979/ | [
"Jianren Wang",
"Ziwen Zhuang",
"Hang Zhao",
"Jianren Wang",
"Ziwen Zhuang",
"Hang Zhao"
] | Efficient exploration is a long-standing problem in reinforcement learning since extrinsic rewards are usually sparse or missing. A popular solution to this issue is to feed an agent with novelty signals as intrinsic rewards. In this work, we introduce SEMI, a self-supervised exploration policy by incentivizing the agent to maximize a new novelty signal: multisensory incongruity, which can be meas... |
Real-Robot Deep Reinforcement Learning: Improving Trajectory Tracking of Flexible-Joint Manipulator with Reference Correction | https://ieeexplore.ieee.org/document/9812023/ | [
"Dmytro Pavlichenko",
"Sven Behnke",
"Dmytro Pavlichenko",
"Sven Behnke"
] | Flexible-joint manipulators are governed by complex nonlinear dynamics, defining a challenging control problem. In this work, we propose an approach to learn an outer-loop joint trajectory tracking controller with deep reinforcement learning. The controller represented by a stochastic policy is learned in under two hours directly on the real robot. This is achieved through bounded reference correc... |
Sequential Joint Shape and Pose Estimation of Vehicles with Application to Automatic Amodal Segmentation Labeling | https://ieeexplore.ieee.org/document/9812202/ | [
"Josephine Monica",
"Wei-Lun Chao",
"Mark Campbell",
"Josephine Monica",
"Wei-Lun Chao",
"Mark Campbell"
] | Shape and pose estimation is a critical perception problem for a self-driving car to fully understand its surrounding environment. One fundamental challenge in solving this problem is the incomplete sensor signal (e.g., LiDAR scans), especially for faraway or occluded objects. In this paper, we propose a novel algorithm to address this challenge, which explicitly leverages the sensor signal captur... |
A Dual-Stream Architecture for Real-Time Morphological Analysis of Aneurysm in Robot-Assisted Minimally Invasive Surgery | https://ieeexplore.ieee.org/document/9812075/ | [
"Yan-Jie Zhou",
"Shi-Qi Liu",
"Xiao-Liang Xie",
"Xiao-Hu Zhou",
"Zeng-Guang Hou",
"Rui-Qi Li",
"Zhen-Liang Ni",
"Chen-Chen Fan",
"Yan-Jie Zhou",
"Shi-Qi Liu",
"Xiao-Liang Xie",
"Xiao-Hu Zhou",
"Zeng-Guang Hou",
"Rui-Qi Li",
"Zhen-Liang Ni",
"Chen-Chen Fan"
] | Real-time and precise morphological analysis of intraoperative AAA is a significant pre-imperative for robot-assisted minimally invasive surgery (RMIS). However, this task is frequently accompanied by the difficulties of ambiguous boundaries and obscured surfaces of aneurysms. To remedy these problems, we propose a Light-Weight Dual-Stream Boundary-Aware Network (DSB-Net) and a novel diagnosis alg... |
Manipulation of unknown objects via contact configuration regulation | https://ieeexplore.ieee.org/document/9811713/ | [
"Neel Doshi",
"Orion Taylor",
"Alberto Rodriguez",
"Neel Doshi",
"Orion Taylor",
"Alberto Rodriguez"
] | We present an approach to robotic manipulation of unknown objects through regulation of the object's contact configuration: the location, geometry, and mode of all contacts between the object, robot, and environment. A contact configu-ration constrains the forces and motions that can be applied to the object; however, synthesizing these constraints generally requires knowledge of the object's pose... |
Physical Property Estimation and Knife Trajectory Optimization During Robotic Cutting | https://ieeexplore.ieee.org/document/9811894/ | [
"Xiaoqian Mu",
"Yan-Bin Jia",
"Xiaoqian Mu",
"Yan-Bin Jia"
] | Dexterous robotic cutting needs to demonstrate a skill level with smooth and efficient knife movements. The work performed by the knife mainly generates fracture and overcomes the blade-material friction. This paper presents a recursive least-squares method that repeatedly estimates relevant physical parameters such as Poisson's ratio, fracture toughness, and coefficient of friction, all varying w... |
RMPs for Safe Impedance Control in Contact-Rich Manipulation | https://ieeexplore.ieee.org/document/9811986/ | [
"Seiji Shaw",
"Ben Abbatematteo",
"George Konidaris",
"Seiji Shaw",
"Ben Abbatematteo",
"George Konidaris"
] | Variable impedance control in operation-space is a promising approach to learning contact-rich manipulation behaviors. One of the main challenges with this approach is producing a manipulation behavior that ensures the safety of the arm and the environment. Such behavior is typically implemented via a reward function that penalizes unsafe actions (e.g. obstacle collision, joint limit extension), b... |
Discovering Synergies for Robot Manipulation with Multi-Task Reinforcement Learning | https://ieeexplore.ieee.org/document/9812170/ | [
"Zhanpeng He",
"Matei Ciocarlie",
"Zhanpeng He",
"Matei Ciocarlie"
] | Controlling robotic manipulators with high-dimensional action spaces for dexterous tasks is a challenging problem. Inspired by human manipulation, researchers have studied generating and using postural synergies for robot hands to accomplish manipulation tasks, leveraging the lower dimensional nature of synergistic action spaces. However, many of these works require pre-collected data from an exis... |
Contact Mode Guided Motion Planning for Quasidynamic Dexterous Manipulation in 3D | https://ieeexplore.ieee.org/document/9811872/ | [
"Xianyi Cheng",
"Eric Huang",
"Yifan Hou",
"Matthew T. Mason",
"Xianyi Cheng",
"Eric Huang",
"Yifan Hou",
"Matthew T. Mason"
] | This paper presents Contact Mode Guided Manipulation Planning (CMGMP) for 3D quasistatic and quasi-dynamic rigid body motion planning in dexterous manipulation. The CMGMP algorithm generates hybrid motion plans including both continuous state transitions and discrete contact mode switches, without the need for pre-specified contact sequences or pre-designed motion primitives. The key idea is to us... |
Learning Purely Tactile In-Hand Manipulation with a Torque-Controlled Hand | https://ieeexplore.ieee.org/document/9812093/ | [
"Leon Sievers",
"Johannes Pitz",
"Berthold Bäuml",
"Leon Sievers",
"Johannes Pitz",
"Berthold Bäuml"
] | We show that a purely tactile dextrous in-hand manipulation task with continuous regrasping, requiring permanent force closure, can be learned from scratch and executed robustly on a torque-controlled humanoid robotic hand. The task is rotating a cube without dropping it, but in contrast to OpenAI's seminal cube manipulation task [1], the palm faces downwards and no cameras but only the hand's pos... |
On the Feasibility of Learning Finger-gaiting In-hand Manipulation with Intrinsic Sensing | https://ieeexplore.ieee.org/document/9812212/ | [
"Gagan Khandate",
"Maximilian Haas-Heger",
"Matei Ciocarlie",
"Gagan Khandate",
"Maximilian Haas-Heger",
"Matei Ciocarlie"
] | Finger-gaiting manipulation is an important skill to achieve large-angle in-hand re-orientation of objects. However, achieving these gaits with arbitrary orientations of the hand is challenging due to the unstable nature of the task. In this work, we use model-free reinforcement learning (RL) to learn finger-gaiting only via precision grasps and demonstrate finger-gaiting for rotation about an axi... |
Negative Stiffness Analysis and Regulation of In-Hand Manipulation with Underactuated Compliant Hands | https://ieeexplore.ieee.org/document/9811964/ | [
"Wenrui Chen",
"Qiang Diao",
"Yaonan Wang",
"Xiaodong Zhou",
"Qiang Zhang",
"Cuo Yan",
"Zhiyong Li",
"Wenrui Chen",
"Qiang Diao",
"Yaonan Wang",
"Xiaodong Zhou",
"Qiang Zhang",
"Cuo Yan",
"Zhiyong Li"
] | This paper addresses the generation mechanism and avoidance method of negative stiffness during in-Hand manipulation with underactuated compliant hands. Firstly, a planar hand with two three-jointed fingers manipulating a rectangular is set, and a quasi-static underactuated operation model is established. Secondly, based on this simulation model, we investigated the stiffness evolution during in-h... |
Robust and Accurate Multi-Agent SLAM with Efficient Communication for Smart Mobiles | https://ieeexplore.ieee.org/document/9812366/ | [
"Jialing Liu",
"Kaiqi Chen",
"Ruyu Liu",
"Yanhong Yang",
"Zhenhua Wang",
"Jianhua Zhang",
"Jialing Liu",
"Kaiqi Chen",
"Ruyu Liu",
"Yanhong Yang",
"Zhenhua Wang",
"Jianhua Zhang"
] | In a long-term large-scenario application, the multi-agent collaborative SLAM is expected to improve the robustness and efficiency of executing tasks for mobile agents. In this paper, a multi-agent collaborative visual-inertial SLAM system is proposed based on a centralized client-server (CS) architecture, where the clients run on smart mobiles. In general, multi-agent collaborative SLAM relies on... |
Synergistic Scheduling of Learning and Allocation of Tasks in Human-Robot Teams | https://ieeexplore.ieee.org/document/9812328/ | [
"Shivam Vats",
"Oliver Kroemer",
"Maxim Likhachev",
"Shivam Vats",
"Oliver Kroemer",
"Maxim Likhachev"
] | We consider the problem of completing a set of $n$ tasks with a human-robot team using minimum effort. In many domains, teaching a robot to be fully autonomous can be counterproductive if there are finitely many tasks to be done. Rather, the optimal strategy is to weigh the cost of teaching a robot and its benefit- how many new tasks it allows the robot to solve autonomously. We formulate this as ... |
Mixed Reality as Communication Medium for Human-Robot Collaboration | https://ieeexplore.ieee.org/document/9812233/ | [
"Simone Macciò",
"Alessandro Carfì",
"Fulvio Mastrogiovanni",
"Simone Macciò",
"Alessandro Carfì",
"Fulvio Mastrogiovanni"
] | Humans engaged in collaborative activities are naturally able to convey their intentions to teammates through multi-modal communication, which is made up of explicit and implicit cues. Similarly, a more natural form of human-robot collaboration may be achieved by enabling robots to convey their intentions to human teammates via multiple communication channels. In this paper, we postulate that a be... |
Adaptive Vision-Based Control of Redundant Robots with Null-Space Interaction for Human-Robot Collaboration | https://ieeexplore.ieee.org/document/9812218/ | [
"Xiangjie Yan",
"Chen Chen",
"Xiang Li",
"Xiangjie Yan",
"Chen Chen",
"Xiang Li"
] | Human-robot collaboration aims to extend human ability through cooperation with robots. This technology is currently helping people with physical disabilities, has transformed the manufacturing process of companies, improved surgical performance, and will likely revolutionize the daily lives of everyone in the future. Being able to enhance the performance of both sides, such that human-robot colla... |
HATP/EHDA: A Robot Task Planner Anticipating and Eliciting Human Decisions and Actions | https://ieeexplore.ieee.org/document/9812227/ | [
"Guilhem Buisan",
"Anthony Favier",
"Amandine Mayima",
"Rachid Alami",
"Guilhem Buisan",
"Anthony Favier",
"Amandine Mayima",
"Rachid Alami"
] | The variety and complexity of tasks autonomous robots can tackle is constantly increasing, yet we seldom see robots collaborating with humans. Indeed, humans are either requested for punctual help or are given the lead on the whole task. We propose a human-aware task planning approach allowing the robot to plan for a task while also considering and emulating the human decision, action, and reactio... |
Dynamic Human-Robot Role Allocation based on Human Ergonomics Risk Prediction and Robot Actions Adaptation | https://ieeexplore.ieee.org/document/9812438/ | [
"Elena Merlo",
"Edoardo Lamon",
"Fabio Fusaro",
"Marta Lorenzini",
"Alessandro Carfi",
"Fulvio Mastrogiovanni",
"Arash Ajoudani",
"Elena Merlo",
"Edoardo Lamon",
"Fabio Fusaro",
"Marta Lorenzini",
"Alessandro Carfi",
"Fulvio Mastrogiovanni",
"Arash Ajoudani"
] | Even though cobots have high potential in bringing several benefits in the manufacturing and logistic processes, their rapid (re-)deployment in changing environments is still limited. To enable fast adaptation to new product demands and to boost the fitness of the human workers to the allocated tasks, we propose a novel method that optimizes assembly strategies and distributes the effort among the... |
Assisting Operators of Articulated Machinery with Optimal Planning and Goal Inference | https://ieeexplore.ieee.org/document/9811864/ | [
"Ehsan Yousefi",
"Dylan P. Losey",
"Inna Sharf",
"Ehsan Yousefi",
"Dylan P. Losey",
"Inna Sharf"
] | Operating an articulated machine is a complex and hierarchical task, involving several levels of decision making. Motivated by the timber-harvesting applications of these machines, we are interested in developing a collaborative framework for operating an articulated machine/robot in order to increase its level of autonomy. In this paper, we consider two problems in the context of collaborative op... |
R2poweR: The Proof-of-Concept of a Backdrivable, High-Ratio Gearbox for Human-Robot Collaboration | https://ieeexplore.ieee.org/document/9811923/ | [
"P. L. Garcia",
"S. Crispel",
"A. Varadharajan",
"E. Saerens",
"T. Verstraten",
"B. Vanderborght",
"D. Lefeber",
"P. L. Garcia",
"S. Crispel",
"A. Varadharajan",
"E. Saerens",
"T. Verstraten",
"B. Vanderborght",
"D. Lefeber"
] | Robotic engineers face major challenges to solve the complex actuation needs of Human-Robot Collaboration with existing act robotic gearboxes. Available technologies comprise high-ratio Planetary Gearheads, Cycloid Drives and Harmonic Drives, inherited from conventional industrial robotics. Alternative approaches include Direct-Drive and Quasi Direct-Drive actuation strategies, which propose to ca... |
All-in-One: A DRL-based Control Switch Combining State-of-the-art Navigation Planners | https://ieeexplore.ieee.org/document/9811797/ | [
"Linh KU+000E4stner",
"Johannes Cox",
"Teham Buiyan",
"Jens Lambrecht",
"Linh KU+000E4stner",
"Johannes Cox",
"Teham Buiyan",
"Jens Lambrecht"
] | Autonomous navigation of mobile robots is an es-sential aspect in use cases such as delivery, assistance or logistics. Although traditional planning methods are well integrated into existing navigation systems, they struggle in highly dynamic en-vironments. On the other hand, Deep-Reinforcement-Learning-based methods show superior performance in dynamic obstacle avoidance but are not suitable for ... |
Trajectory Prediction with Linguistic Representations | https://ieeexplore.ieee.org/document/9811928/ | [
"Yen-Ling Kuo",
"Xin Huang",
"Andrei Barbu",
"Stephen G. McGill",
"Boris Katz",
"John J. Leonard",
"Guy Rosman",
"Yen-Ling Kuo",
"Xin Huang",
"Andrei Barbu",
"Stephen G. McGill",
"Boris Katz",
"John J. Leonard",
"Guy Rosman"
] | Language allows humans to build mental models that interpret what is happening around them resulting in more accurate long-term predictions. We present a novel trajectory prediction model that uses linguistic intermediate representations to forecast trajectories, and is trained using trajectory samples with partially-annotated captions. The model learns the meaning of each of the words without dir... |
Game-Theoretic Planning for Autonomous Driving among Risk-Aware Human Drivers | https://ieeexplore.ieee.org/document/9811865/ | [
"Rohan Chandra",
"Mingyu Wang",
"Mac Schwager",
"Dinesh Manocha",
"Rohan Chandra",
"Mingyu Wang",
"Mac Schwager",
"Dinesh Manocha"
] | We present a novel approach for risk-aware planning with human agents in multi-agent traffic scenarios. Our approach takes into account the wide range of human driver behaviors on the road, from aggressive maneuvers like speeding and overtaking, to conservative traits like driving slowly and conforming to the right-most lane. In our approach, we learn a mapping from a data-driven human driver beha... |
Deploying Traffic Smoothing Cruise Controllers Learned from Trajectory Data | https://ieeexplore.ieee.org/document/9811912/ | [
"Nathan Lichtlé",
"Eugene Vinitsky",
"Matthew Nice",
"Benjamin Seibold",
"Dan Work",
"Alexandre M. Bayen",
"Nathan Lichtlé",
"Eugene Vinitsky",
"Matthew Nice",
"Benjamin Seibold",
"Dan Work",
"Alexandre M. Bayen"
] | Autonomous vehicle-based traffic smoothing con-trollers are often not transferred to real-world use due to challenges in calibrating many-agent traffic simulators. We show a pipeline to sidestep such calibration issues by collecting trajectory data and learning controllers directly from trajectory data that are then deployed zero-shot onto the highway. We construct a dataset of 772.3 kilometers of... |
Personalized Car Following for Autonomous Driving with Inverse Reinforcement Learning | https://ieeexplore.ieee.org/document/9812446/ | [
"Zhouqiao Zhao",
"Ziran Wang",
"Kyungtae Han",
"Rohit Gupta",
"Prashant Tiwari",
"Guoyuan Wu",
"Matthew J. Barth",
"Zhouqiao Zhao",
"Ziran Wang",
"Kyungtae Han",
"Rohit Gupta",
"Prashant Tiwari",
"Guoyuan Wu",
"Matthew J. Barth"
] | Driving automation is gradually replacing human driving maneuvers in different applications such as adaptive cruise control and lane keeping. However, contemporary driving automation applications based on expert systems or prede-fined control strategies are not in line with individual human driver's preference. To overcome this problem, we propose a Personalized Adaptive Cruise Control (P-ACC) sys... |
HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling | https://ieeexplore.ieee.org/document/9812254/ | [
"Xin Huang",
"Guy Rosman",
"Igor Gilitschenski",
"Ashkan Jasour",
"Stephen G. McGill",
"John J. Leonard",
"Brian C. Williams",
"Xin Huang",
"Guy Rosman",
"Igor Gilitschenski",
"Ashkan Jasour",
"Stephen G. McGill",
"John J. Leonard",
"Brian C. Williams"
] | Modeling multi-modal high-level intent is important for ensuring diversity in trajectory prediction. Existing approaches explore the discrete nature of human intent before predicting continuous trajectories, to improve accuracy and support explainability. However, these approaches often assume the intent to remain fixed over the prediction horizon, which is problematic in practice, especially over... |
Important Object Identification with Semi-Supervised Learning for Autonomous Driving | https://ieeexplore.ieee.org/document/9812234/ | [
"Jiachen Li",
"Haiming Gang",
"Hengbo Ma",
"Masayoshi Tomizuka",
"Chiho Choi",
"Jiachen Li",
"Haiming Gang",
"Hengbo Ma",
"Masayoshi Tomizuka",
"Chiho Choi"
] | Accurate identification of important objects in the scene is a prerequisite for safe and high-quality decision making and motion planning of intelligent agents (e.g., autonomous vehicles) that navigate in complex and dynamic environments. Most existing approaches attempt to employ attention mechanisms to learn importance weights associated with each object indirectly via various tasks (e.g., traje... |
BAANet: Learning Bi-directional Adaptive Attention Gates for Multispectral Pedestrian Detection | https://ieeexplore.ieee.org/document/9811999/ | [
"Xiaoxiao Yang",
"Yeqiang Qian",
"Huijie Zhu",
"Chunxiang Wang",
"Ming Yang",
"Xiaoxiao Yang",
"Yeqiang Qian",
"Huijie Zhu",
"Chunxiang Wang",
"Ming Yang"
] | Thermal infrared (TIR) image has proven effectiveness in providing temperature cues to the RGB features for multispectral pedestrian detection. Most existing methods directly inject the TIR modality into the RGB-based framework or simply ensemble the results of two modalities. This, however, could lead to inferior detection performance, as the RGB and TIR features generally have modality-specific ... |
Globally Optimal Relative Pose Estimation for Multi-Camera Systems with Known Gravity Direction | https://ieeexplore.ieee.org/document/9812380/ | [
"Qianliang Wu",
"Yaqing Ding",
"Xinlei Qi",
"Jin Xie",
"Jian Yang",
"Qianliang Wu",
"Yaqing Ding",
"Xinlei Qi",
"Jin Xie",
"Jian Yang"
] | Multiple-camera systems have been widely used in self-driving cars, robots, and smartphones. In addition, they are typically also equipped with IMUs (inertial measurement units). Using the gravity direction extracted from the IMU data, the y-axis of the body frame of the multi-camera system can be aligned with this common direction, reducing the original three degree-of-freedom(DOF) relative rotat... |
Robotic Manipulators Performing Smart Sanding Operation: A Vibration Approach | https://ieeexplore.ieee.org/document/9812029/ | [
"Joshua Nguyen",
"Manuel Bailey",
"Ignacio Carlucho",
"Corina Barbalata",
"Joshua Nguyen",
"Manuel Bailey",
"Ignacio Carlucho",
"Corina Barbalata"
] | This paper presents the design of a novel expert system for robotic manipulators performing sanding tasks on work surfaces. The expert system adjusts the velocity of the robotic manipulator based on the observed surface quality. These observation are obtained by an analysis of the raw force data provided by a force-torque sensor at the end-effector level. The expert system consists of two governin... |
Learning to Fill the Seam by Vision: Sub-millimeter Peg-in-hole on Unseen Shapes in Real World | https://ieeexplore.ieee.org/document/9812429/ | [
"Liang Xie",
"Hongxiang Yu",
"Yinghao Zhao",
"Haodong Zhang",
"Zhongxiang Zhou",
"Minhang Wang",
"Yue Wang",
"Rong Xiong",
"Liang Xie",
"Hongxiang Yu",
"Yinghao Zhao",
"Haodong Zhang",
"Zhongxiang Zhou",
"Minhang Wang",
"Yue Wang",
"Rong Xiong"
] | In the peg insertion task, human pays attention to the seam between the peg and the hole and tries to fill it continuously with visual feedback. By imitating the human's behavior, we design architectures with position and orientation estimators based on the seam representation for pose alignment, which proves to be general to the unseen peg geometries. By putting the estimators into the closed-loo... |
An Experimental Study of Wind Resistance and Power Consumption in MAVs with a Low-Speed Multi-Fan Wind System | https://ieeexplore.ieee.org/document/9811834/ | [
"Diana A. Olejnik",
"Sunyi Wang",
"Julien Dupeyroux",
"Stein Stroobants",
"Matej Karasek",
"Christophe De Wagter",
"Guido de Croon",
"Diana A. Olejnik",
"Sunyi Wang",
"Julien Dupeyroux",
"Stein Stroobants",
"Matej Karasek",
"Christophe De Wagter",
"Guido de Croon"
] | This paper discusses a low-cost, open-source and open-hardware design and performance evaluation of a low-speed, multi-fan wind system dedicated to micro air vehicle (MAV) testing. In addition, a set of experiments with a flapping wing MAV and rotorcraft is presented, demonstrating the capabilities of the system and the properties of these different types of drones in response to various types of ... |
dSEDA: a Differential Series Elastic Damped Actuator | https://ieeexplore.ieee.org/document/9811727/ | [
"Simone Monteleone",
"Francesca Negrello",
"Giorgio Grioli",
"Manuel G. Catalano",
"Simone Monteleone",
"Francesca Negrello",
"Giorgio Grioli",
"Manuel G. Catalano"
] | Compliant actuation bestows robots with the ability to cope with unstructured environments, move with agility, and interact safely with humans at the expense of reduced tracking accuracy. The inclusion of dampening components aims to reduce oscillatory dynamics and partially restore precision without sacrificing the previously obtained characteristics. This paper introduces the concept and design ... |
Amplitude Control for Parallel Lattices of Docked Modboats | https://ieeexplore.ieee.org/document/9812381/ | [
"Gedaliah Knizhnik",
"Mark Yim",
"Gedaliah Knizhnik",
"Mark Yim"
] | The Modboat is a low-cost, underactuated, modular robot capable of surface swimming. It is able to swim individually, dock to other Modboats, and undock from them using only a single motor and two passive flippers. Undocking without additional actuation is achieved by causing intentional self-collision between the tails of neighboring modules; this becomes a challenge when group swimming as one co... |
Sliding Mode Controller for Positioning of an Underwater Vehicle Subject to Disturbances and Time Delays | https://ieeexplore.ieee.org/document/9812005/ | [
"Harun Tugal",
"Kamil Cetin",
"Xiaoran Han",
"Ibrahim Kucukdemiral",
"Joshua Roe",
"Yvan Petillot",
"M. Suphi Erden",
"Harun Tugal",
"Kamil Cetin",
"Xiaoran Han",
"Ibrahim Kucukdemiral",
"Joshua Roe",
"Yvan Petillot",
"M. Suphi Erden"
] | Unmanned underwater vehicles are crucial for deep-sea exploration and inspection without imposing any danger to human life due to extreme environmental conditions. But, designing a robust controller that can cope with model uncertainties, external disturbances, and time delays for such vehicles is a challenge. This paper implements a sliding mode position control algorithm with a time-delay estima... |
HoloOcean: An Underwater Robotics Simulator | https://ieeexplore.ieee.org/document/9812353/ | [
"Easton Potokar",
"Spencer Ashford",
"Michael Kaess",
"Joshua G. Mangelson",
"Easton Potokar",
"Spencer Ashford",
"Michael Kaess",
"Joshua G. Mangelson"
] | Due to the difficulty and expense of underwater field trials, a high fidelity underwater simulator is a necessity for testing and developing algorithms. To fill this need, we present HoloOcean, an open source underwater simulator, built upon Unreal Engine 4 (UE4). HoloOcean comes equipped with multi-agent support, various sensor implementations of common underwater sensors, and simulated communica... |
Flow-Based Control of Marine Robots in Gyre-Like Environments | https://ieeexplore.ieee.org/document/9812331/ | [
"Gedaliah Knizhnik",
"Peihan Li",
"Xi Yu",
"M. Ani Hsieh",
"Gedaliah Knizhnik",
"Peihan Li",
"Xi Yu",
"M. Ani Hsieh"
] | We present a flow-based control strategy that enables resource-constrained marine robots to patrol gyre-like flow environments on an orbital trajectory with a periodicity in a given range. The controller does not require a detailed model of the flow field and relies only on the robot's location relative to the center of the gyre. Instead of precisely tracking a pre-defined trajectory, the robots a... |
Spatial Acoustic Projection for 3D Imaging Sonar Reconstruction | https://ieeexplore.ieee.org/document/9812277/ | [
"Sascha Arnold",
"Bilal Wehbe",
"Sascha Arnold",
"Bilal Wehbe"
] | In this work we present a novel method for reconstructing 3D surfaces using a multi-beam imaging sonar. We integrate the intensities measured by the sonar from different viewpoints for fixed cell positions in a 3D grid. For each cell we integrate a feature vector that holds the mean intensity for a discretized range of viewpoints. Based on the feature vectors and independent sparse range measureme... |
An Integrated Design Pipeline for Tactile Sensing Robotic Manipulators | https://ieeexplore.ieee.org/document/9812335/ | [
"Lara Zlokapa",
"Yiyue Luo",
"Jie Xu",
"Michael Foshey",
"Kui Wu",
"Pulkit Agrawal",
"Wojciech Matusik",
"Lara Zlokapa",
"Yiyue Luo",
"Jie Xu",
"Michael Foshey",
"Kui Wu",
"Pulkit Agrawal",
"Wojciech Matusik"
] | Traditional robotic manipulator design methods require extensive, time-consuming, and manual trial and error to produce a viable design. During this process, engineers often spend their time redesigning or reshaping components as they discover better topologies for the robotic manipula-tor. Tactile sensors, while useful, often complicate the design due to their bulky form factor. We propose an int... |
Graph Grammar-Based Automatic Design for Heterogeneous Fleets of Underwater Robots | https://ieeexplore.ieee.org/document/9811808/ | [
"Allan Zhao",
"Jie Xu",
"Juan Salazar",
"Wei Wang",
"Pingchuan Ma",
"Daniela Rus",
"Wojciech Matusik",
"Allan Zhao",
"Jie Xu",
"Juan Salazar",
"Wei Wang",
"Pingchuan Ma",
"Daniela Rus",
"Wojciech Matusik"
] | Autonomous underwater vehicles (AUVs) are spe-cialized robots that are commonly used for seafloor surveying and ocean water sampling. Computational design approaches have emerged to reduce the effort required to design both individual AUVs as well as fleets. As the number and scale of underwater missions increases beyond the capabilities of a single vehicle, fleet level design will become more imp... |
The Design of Stretch: A Compact, Lightweight Mobile Manipulator for Indoor Human Environments | https://ieeexplore.ieee.org/document/9811922/ | [
"Charles C. Kemp",
"Aaron Edsinger",
"Henry M. Clever",
"Blaine Matulevich",
"Charles C. Kemp",
"Aaron Edsinger",
"Henry M. Clever",
"Blaine Matulevich"
] | Mobile manipulators for indoor human environments can serve as versatile devices that perform a variety of tasks, yet adoption of this technology has been limited. Reducing size, weight, and cost could facilitate adoption, but risks restricting capabilities. We present a novel design that reduces size, weight, and cost, while supporting a variety of tasks. The core design consists of a two-wheeled... |
Orientation to Pose: Continuum Robots Shape Reconstruction Based on the Multi-Attitude Solving Approach | https://ieeexplore.ieee.org/document/9812289/ | [
"Hao Cheng",
"Hejie Xu",
"Hongji Shang",
"Xueqian Wang",
"Houde Liu",
"Bin Liang",
"Hao Cheng",
"Hejie Xu",
"Hongji Shang",
"Xueqian Wang",
"Houde Liu",
"Bin Liang"
] | Continuum robots are typically slender and flexible with infinite freedoms in theory, which poses a challenge for their control and application. The shape reconstruction of continuum robots is vital to realize closed-loop control. This paper proposes a novel general real-time shape reconstruction framework of continuum robots based on the piecewise polynomial curvature (PPC) kinematics model. We i... |
A Novel Full State Feedback Decoupling Controller For Elastic Robot Arm | https://ieeexplore.ieee.org/document/9812047/ | [
"Hongxi Zhu",
"Ulrike Thomas",
"Hongxi Zhu",
"Ulrike Thomas"
] | In this paper a novel full state feedback approach for control of compliant actuated robot with nonlinear spring characteristics is presented. A multi-DOF elastic robot arm is a multi-input multi-output (MIMO) under-actuated system. By the new novel controller, which is based on motor coordinate transformation and motor inertia shaping, the MIMO system can be converted into a set of decoupled sing... |
3D Printing of Concrete with a Continuum Robot Hose Using Variable Curvature Kinematics | https://ieeexplore.ieee.org/document/9812123/ | [
"Manu Srivastava",
"Jake Ammons",
"Abdul B. Peerzada",
"Venkat N. Krovi",
"Prasad Rangaraju",
"Ian D. Walker",
"Manu Srivastava",
"Jake Ammons",
"Abdul B. Peerzada",
"Venkat N. Krovi",
"Prasad Rangaraju",
"Ian D. Walker"
] | We present a novel application of continuum robots acting as concrete hoses to support 3D printing of cementitious materials. An industrial concrete hose was fitted with a cable harness and remotely actuated via tendons. The resulting continuum hose robot exhibited non constant curvature. In order to account for this, a new geometric approach to modeling variable curvature inverse kinematics using... |
Modeling the dynamics of soft robots by discs and threads | https://ieeexplore.ieee.org/document/9812286/ | [
"Joshua A. Schultz",
"Haley Sanders",
"Phuc Duc Hong Bui",
"Brett Layer",
"Marc Killpack",
"Joshua A. Schultz",
"Haley Sanders",
"Phuc Duc Hong Bui",
"Brett Layer",
"Marc Killpack"
] | In this paper, we propose a new tractable ordinary differential equation formulation for dynamic simulation of fabric- reinforced inflatable soft robots. The method performs a lumped-parameter discretization of the continuum robot into discrete discs (inertia), spring elements, and threads (representing the inextensible fabric reinforcement). Using the repetition in the structure of the Lagrangian... |
A Recurrent Differentiable Engine for Modeling Tensegrity Robots Trainable with Low-Frequency Data | https://ieeexplore.ieee.org/document/9812135/ | [
"Kun Wang",
"Mridul Aanjaneya",
"Kostas Bekris",
"Kun Wang",
"Mridul Aanjaneya",
"Kostas Bekris"
] | Tensegrity robots, composed of rigid rods and flexible cables, are difficult to accurately model and control given the presence of complex dynamics and high number of DoFs. Differentiable physics engines have been recently proposed as a data-driven approach for model identification of such complex robotic systems. These engines are often executed at a high-frequency to achieve accurate simulation.... |
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