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Cross Domain Robot Imitation with Invariant Representation | https://ieeexplore.ieee.org/document/9811668/ | [
"Zhao-Heng Yin",
"Lingfeng Sun",
"Hengbo Ma",
"Masayoshi Tomizuka",
"Wu-Jun Li",
"Zhao-Heng Yin",
"Lingfeng Sun",
"Hengbo Ma",
"Masayoshi Tomizuka",
"Wu-Jun Li"
] | Animals are able to imitate each others' behavior, despite their difference in biomechanics. In contrast, imitating other similar robots is a much more challenging task in robotics. This problem is called cross domain imitation learning (CDIL). In this paper, we consider CDIL on a class of similar robots. We tackle this problem by introducing an imitation learning algorithm based on invariant repr... |
Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC | https://ieeexplore.ieee.org/document/9812122/ | [
"Andrea Tagliabue",
"Dong-Ki Kim",
"Michael Everett",
"Jonathan P. How",
"Andrea Tagliabue",
"Dong-Ki Kim",
"Michael Everett",
"Jonathan P. How"
] | We propose a demonstration-efficient strategy to compress a computationally expensive Model Predictive Controller (MPC) into a more computationally efficient representation based on a deep neural network and Imitation Learning (IL). By generating a Robust Tube variant (RTMPC) of the MPC and leveraging properties from the tube, we introduce a data augmentation method that enables high demonstration... |
Weakly Supervised Correspondence Learning | https://ieeexplore.ieee.org/document/9811729/ | [
"Zihan Wang",
"Zhangjie Cao",
"Yilun Hao",
"Dorsa Sadigh",
"Zihan Wang",
"Zhangjie Cao",
"Yilun Hao",
"Dorsa Sadigh"
] | Correspondence learning is a fundamental problem in robotics, which aims to learn a mapping between state, action pairs of agents of different dynamics or embodiments. However, current correspondence learning methods either leverage strictly paired data-which are often difficult to collect-or learn in an unsupervised fashion from unpaired data using regularization techniques such as cycle-consiste... |
JST: Joint Self-training for Unsupervised Domain Adaptation on 2D&3D Object Detection | https://ieeexplore.ieee.org/document/9811975/ | [
"Guangyao Ding",
"Meiying Zhang",
"E Li",
"Qi Hao",
"Guangyao Ding",
"Meiying Zhang",
"E Li",
"Qi Hao"
] | 2D&3D object detection always suffers from a dramatic performance drop when transferring the model trained in the source domain to the target domain due to various domain shifts. In this paper, we propose a Joint Self-Training (JST) framework to improve 2D image and 3D point cloud detectors with aligned outputs simultaneously during the transferring. The proposed framework contains three novelties... |
Learning Spatiotemporal Occupancy Grid Maps for Lifelong Navigation in Dynamic Scenes | https://ieeexplore.ieee.org/document/9812297/ | [
"Hugues Thomas",
"Matthieu Gallet de Saint Aurin",
"Jian Zhang",
"Timothy D. Barfoot",
"Hugues Thomas",
"Matthieu Gallet de Saint Aurin",
"Jian Zhang",
"Timothy D. Barfoot"
] | We present a novel method for generating, predicting, and using Spatiotemporal Occupancy Grid Maps (SOGM), which embed future information of dynamic scenes. Our au-tomated generation process creates groundtruth SOGMs from previous navigation data. We build on prior work to annotate lidar points based on their dynamic properties, which are then projected on time-stamped 2D grids: SOGMs. We design a... |
Kinematic Structure Estimation of Arbitrary Articulated Rigid Objects for Event Cameras | https://ieeexplore.ieee.org/document/9812430/ | [
"Urbano Miguel Nunes",
"Yiannis Demiris",
"Urbano Miguel Nunes",
"Yiannis Demiris"
] | We propose a novel method that estimates the Kinematic Structure (KS) of arbitrary articulated rigid objects from event-based data. Event cameras are emerging sensors that asynchronously report brightness changes with a time resolution of microseconds, making them suitable candidates for motion-related perception. By assuming that an articulated rigid object is composed of body parts whose shape c... |
Incremental Learning for Enhanced Personalization of Autocomplete Teleoperation | https://ieeexplore.ieee.org/document/9812108/ | [
"Mohammad Haj Hussein",
"Batool Ibrahim",
"Imad H. Elhajj",
"Daniel Asmar",
"Mohammad Haj Hussein",
"Batool Ibrahim",
"Imad H. Elhajj",
"Daniel Asmar"
] | Remote controlling robots without any automated help is difficult due to various limitations. Autocomplete mitigates this difficulty by automatically detecting and completing the intended motions on robots from the input of the user. Such an approach can improve the system performance and reduce the load on the operator. Usually, recognizing intended motions is achieved using pre-trained Deep Lear... |
Learning to Detect Slip with Barometric Tactile Sensors and a Temporal Convolutional Neural Network | https://ieeexplore.ieee.org/document/9811592/ | [
"Abhinav Grover",
"Philippe Nadeau",
"Christopher Grebe",
"Jonathan Kelly",
"Abhinav Grover",
"Philippe Nadeau",
"Christopher Grebe",
"Jonathan Kelly"
] | The ability to perceive object slip via tactile feedback enables humans to accomplish complex manipulation tasks including maintaining a stable grasp. Despite the utility of tactile information for many applications, tactile sensors have yet to be widely deployed in industrial robotics settings; part of the challenge lies in identifying slip and other events from the tactile data stream. In this p... |
Meta-path Analysis on Spatio-Temporal Graphs for Pedestrian Trajectory Prediction | https://ieeexplore.ieee.org/document/9811632/ | [
"Aamir Hasan",
"Pranav Sriram",
"Katherine Driggs-Campbell",
"Aamir Hasan",
"Pranav Sriram",
"Katherine Driggs-Campbell"
] | Spatio-temporal graphs (ST-graphs) have been used to model time series tasks such as traffic forecasting, human motion modeling, and action recognition. The high-level structure and corresponding features from ST-graphs have led to improved performance over traditional architectures. However, current methods tend to be limited by simple features, despite the rich information provided by the full g... |
Interleaving Monte Carlo Tree Search and Self-Supervised Learning for Object Retrieval in Clutter | https://ieeexplore.ieee.org/document/9812132/ | [
"Baichuan Huang",
"Teng Guo",
"Abdeslam Boularias",
"Jingjin Yu",
"Baichuan Huang",
"Teng Guo",
"Abdeslam Boularias",
"Jingjin Yu"
] | In this study, working with the task of object retrieval in clutter, we have developed a robot learning framework in which Monte Carlo Tree Search (MCTS) is first applied to enable a Deep Neural Network (DNN) to learn the intricate interactions between a robot arm and a complex scene containing many objects, allowing the DNN to partially clone the behavior of MCTS. In turn, the trained DNN is inte... |
RepAr-Net: Re-Parameterized Encoders and Attentive Feature Arsenals for Fast Video Denoising | https://ieeexplore.ieee.org/document/9812394/ | [
"S P Sharan",
"Adithya K Krishna",
"A Siddharth Rao",
"Varun P Gopi",
"S P Sharan",
"Adithya K Krishna",
"A Siddharth Rao",
"Varun P Gopi"
] | Real-time video denoising finds applications in several fields like mobile robotics, satellite television, and surveillance systems. Traditional denoising approaches are more common in such systems than their deep learning-based counterparts despite their inferior performance. The large size and heavy computational requirements of neural network-based denoising models pose a serious impediment to ... |
A User-customized Automatic Music Composition System | https://ieeexplore.ieee.org/document/9812396/ | [
"Fan Mo",
"Xiaoqiang Ji",
"Huihuan Qian",
"Yangsheng Xu",
"Fan Mo",
"Xiaoqiang Ji",
"Huihuan Qian",
"Yangsheng Xu"
] | This paper introduces an intelligent system which composes music following the users' instructions. Current auto-matic music generation models are lack of stability. Meanwhile, they cannot satisfy the preference of different people. To overcome these challenges, we train a Transformer-based neural network to generate short music segments using a dataset. A user can compose music pieces by interact... |
KEMP: Keyframe-Based Hierarchical End-to-End Deep Model for Long- Term Trajectory Prediction | https://ieeexplore.ieee.org/document/9812337/ | [
"Qiujing Lu",
"Weiqiao Han",
"Jeffrey Ling",
"Minfa Wang",
"Haoyu Chen",
"Balakrishnan Varadarajan",
"Paul Covington",
"Qiujing Lu",
"Weiqiao Han",
"Jeffrey Ling",
"Minfa Wang",
"Haoyu Chen",
"Balakrishnan Varadarajan",
"Paul Covington"
] | Predicting future trajectories of road agents is a critical task for autonomous driving. Recent goal-based trajectory prediction methods, such as DenseTNT and PECNet [1], [2], have shown good performance on prediction tasks on public datasets. However, they usually require complicated goal-selection algorithms and optimization. In this work, we propose KEMP, a hierarchical end-to-end deep learning... |
Narrowing the coordinate-frame gap in behavior prediction models: Distillation for efficient and accurate scene-centric motion forecasting | https://ieeexplore.ieee.org/document/9812368/ | [
"DiJia Andy Su",
"Bertrand Douillard",
"Rami Al-Rfou",
"Cheol Park",
"Benjamin Sapp",
"DiJia Andy Su",
"Bertrand Douillard",
"Rami Al-Rfou",
"Cheol Park",
"Benjamin Sapp"
] | Behavior prediction models have proliferated in recent years, especially in the popular real-world robotics application of autonomous driving, where representing the distribution over possible futures of moving agents is essential for safe and comfortable motion planning. In these models, the choice of coordinate frames to represent inputs and outputs has crucial trade offs which broadly fall into... |
SEHLNet: Separate Estimation of High- and Low-Frequency components for Depth Completion | https://ieeexplore.ieee.org/document/9811840/ | [
"Qiang Liu",
"Haosong Yue",
"Zhanggang Lyu",
"Wei Wang",
"Zhong Liu",
"Weihai Chen",
"Qiang Liu",
"Haosong Yue",
"Zhanggang Lyu",
"Wei Wang",
"Zhong Liu",
"Weihai Chen"
] | Depth completion refers to inferring the dense depth map from a sparse depth map with or without corre-sponding color image. Numerous neural networks have been proposed to accomplish this task. However, insufficient uti-lization of heteromorphic data and the fact that predicted dense depth prefers a sparse depth enormously damage the performance of approaches. To reduce data preference and fully u... |
Visually Grounding Language Instruction for History-Dependent Manipulation | https://ieeexplore.ieee.org/document/9812279/ | [
"Hyemin Ahn",
"Obin Kwon",
"Kyungdo Kim",
"Jaeyeon Jeong",
"Howoong Jun",
"Hongjung Lee",
"Dongheui Lee",
"Songhwai Oh",
"Hyemin Ahn",
"Obin Kwon",
"Kyungdo Kim",
"Jaeyeon Jeong",
"Howoong Jun",
"Hongjung Lee",
"Dongheui Lee",
"Songhwai Oh"
] | This paper emphasizes the importance of a robot's ability to refer to its task history, especially when it exe-cutes a series of pick-and-place manipulations by following language instructions given one by one. The advantage of referring to the manipulation history can be categorized into two folds: (1) the language instructions omitting details but using expressions referring to the past can be i... |
PF-MOT: Probability Fusion Based 3D Multi-Object Tracking for Autonomous Vehicles | https://ieeexplore.ieee.org/document/9811653/ | [
"Tao Wen",
"Yanyong Zhang",
"Nikolaos M. Freris",
"Tao Wen",
"Yanyong Zhang",
"Nikolaos M. Freris"
] | 3D Multi-Object Tracking (MOT) plays a crucial role in efficient and safe operation of automatic driving, especially in scenarios of occlusion or poor visibility. Most 3D MOT methods leverage only positional distance, which is insufficient for scenes with high density of objects or drastic changes in the motion state. In order to address this, we propose a new 3D MOT model which fuses information ... |
Powerful and dexterous multi-finger hand using dynamical pulley mechanism | https://ieeexplore.ieee.org/document/9812112/ | [
"Tadaaki Hasegawa",
"Hironori Waita",
"Tomohiro Kawakami",
"Yoshinari Takemura",
"Tetsuya Ishikawa",
"Yuta Kimura",
"Chiaki Tanaka",
"Kenichiro Sugiyama",
"Takahide Yoshiike",
"Tadaaki Hasegawa",
"Hironori Waita",
"Tomohiro Kawakami",
"Yoshinari Takemura",
"Tetsuya Ishikawa",
"Yuta Kimura",
"Chiaki Tanaka",
"Kenichiro Sugiyama",
"Takahide Yoshiike"
] | A multi-fingered hand that can grasp and manipulate a variety of objects is an option for assisting people in their daily lives. However, the range of torque output that can be handled by the multi-fingered hand is very limited compared to the capability of the human hand. In this paper, we introduce a new multi-fingered hand consisting of a dynamic pulley and a linkage mechanism, aiming to achiev... |
HGC-Net: Deep Anthropomorphic Hand Grasping in Clutter | https://ieeexplore.ieee.org/document/9811756/ | [
"Yiming Li",
"Wei Wei",
"Daheng Li",
"Peng Wang",
"Wanyi Li",
"Jun Zhong",
"Yiming Li",
"Wei Wei",
"Daheng Li",
"Peng Wang",
"Wanyi Li",
"Jun Zhong"
] | Grasping in cluttered environments is one of the most fundamental skills in robotic manipulation. Most of the current works focus on estimating grasp poses for parallel-jaw or suction-cup end effectors. However, the study for dexterous anthropomorphic hand grasping in clutter remains a great challenge. In this paper, we propose HGC-Net, a single-shot network that learns to predict dense hand grasp... |
Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Loss | https://ieeexplore.ieee.org/document/9811685/ | [
"Xinghao Zhu",
"Yefan Zhou",
"Yongxiang Fan",
"Lingfeng Sun",
"Jianyu Chen",
"Masayoshi Tomizuka",
"Xinghao Zhu",
"Yefan Zhou",
"Yongxiang Fan",
"Lingfeng Sun",
"Jianyu Chen",
"Masayoshi Tomizuka"
] | Robotic grasping for a diverse set of objects is essential in many robot manipulation tasks. One promising approach is to learn deep grasping models from large training datasets of object images and grasp labels. However, empirical grasping datasets are typically sparsely labeled (i.e., a small number of successful grasp labels**Labels refer to marking the image to indicate a successful robotic gr... |
Multi-Dimensional Compliance of Soft Grippers Enables Gentle Interaction with Thin, Flexible Objects | https://ieeexplore.ieee.org/document/9812324/ | [
"Clark B. Teeple",
"Justin Werfel",
"Robert J. Wood",
"Clark B. Teeple",
"Justin Werfel",
"Robert J. Wood"
] | In this paper, we discuss the role of gripper compliance in successful grasping and manipulation of thin, flexible materials. We show, both conceptually and empirically, that each axis of compliance in a planar gripper provides unique benefits in this domain. Vertical compliance allows robust grasping of thin materials in the presence of large uncertainty in positioning. Lateral compliance increas... |
Grasp Transfer for Deformable Objects by Functional Map Correspondence | https://ieeexplore.ieee.org/document/9812141/ | [
"Cristiana De Farias",
"Brahim Tamadazte",
"Rustam Stolkin",
"Naresh Marturi",
"Cristiana De Farias",
"Brahim Tamadazte",
"Rustam Stolkin",
"Naresh Marturi"
] | Handling object deformations for robotic grasping is still a major problem to solve. In this paper, we propose an efficient learning-free solution for this problem where generated grasp hypotheses of a region of an object are adapted to its deformed configurations. To this end, we investigate the applicability of functional map (FM) correspondence, where the shape matching problem is treated as se... |
Learning Object Relations with Graph Neural Networks for Target-Driven Grasping in Dense Clutter | https://ieeexplore.ieee.org/document/9811601/ | [
"Xibai Lou",
"Yang Yang",
"Changhyun Choi",
"Xibai Lou",
"Yang Yang",
"Changhyun Choi"
] | Robots in the real world frequently come across identical objects in dense clutter. When evaluating grasp poses in these scenarios, a target-driven grasping system requires knowledge of spatial relations between scene objects (e.g., proximity, adjacency, and occlusions). To efficiently complete this task, we propose a target-driven grasping system that simultaneously considers object relations and... |
Learning to Pick by Digging: Data-Driven Dig-Grasping for Bin Picking from Clutter | https://ieeexplore.ieee.org/document/9811736/ | [
"Chao Zhao",
"Zhekai Tong",
"Juan Rojas",
"Jungwon Seo",
"Chao Zhao",
"Zhekai Tong",
"Juan Rojas",
"Jungwon Seo"
] | We present a data-driven approach for effective bin picking from clutter. Recent bin picking solutions usually lead to a direct pinch grasp on a target object without addressing any other potential contact interaction in clutter. However, appropriate physical interaction can be essential to successful singulation and subsequent secure picking, the goal of bin picking. In this work, we contribute a... |
Automatic Acquisition of a Repertoire of Diverse Grasping Trajectories through Behavior Shaping and Novelty Search | https://ieeexplore.ieee.org/document/9811837/ | [
"Aurélien Morel",
"Yakumo Kunimoto",
"Alex Coninx",
"Stéphane Doncieux",
"Aurélien Morel",
"Yakumo Kunimoto",
"Alex Coninx",
"Stéphane Doncieux"
] | Grasping a particular object may require a dedicated grasping movement that may also be specific to the robot end-effector. No generic and autonomous method does exist to generate these movements without making hypotheses on the robot or on the object. Learning methods could help to autonomously discover relevant grasping movements, but they face an important issue: grasping movements are so rare ... |
FFHNet: Generating Multi-Fingered Robotic Grasps for Unknown Objects in Real-time | https://ieeexplore.ieee.org/document/9811666/ | [
"Vincent Mayer",
"Qian Feng",
"Jun Deng",
"Yunlei Shi",
"Zhaopeng Chen",
"Alois Knoll",
"Vincent Mayer",
"Qian Feng",
"Jun Deng",
"Yunlei Shi",
"Zhaopeng Chen",
"Alois Knoll"
] | Grasping unknown objects with multi-fingered hands at high success rates and in real-time is an unsolved problem. Existing methods are limited in the speed of grasp synthesis or the ability to synthesize a variety of grasps from the same observation. We introduce Five-finger Hand Net (FFHNet), an ML model which can generate a wide variety of high-quality multi-fingered grasps for unseen objects fr... |
A Force-Sensitive Grasping Controller Using Tactile Gripper Fingers and an Industrial Position-Controlled Robot | https://ieeexplore.ieee.org/document/9812278/ | [
"Volker Gabler",
"Gerold Huber",
"Dirk Wollherr",
"Volker Gabler",
"Gerold Huber",
"Dirk Wollherr"
] | Grasping fragile objects in the presence of un-certainty is a crucial task for robots, that becomes inherently challenging if the manipulator in use is an industrial robot platform that does not provide compliant control inputs. This requires not only to estimate the alignment error during object contact but also to alter the robot configuration to decrease this error while taking interaction cons... |
Multi-Object Grasping - Types and Taxonomy | https://ieeexplore.ieee.org/document/9812388/ | [
"Yu Sun",
"Eliza Amatova",
"Tianze Chen",
"Yu Sun",
"Eliza Amatova",
"Tianze Chen"
] | This paper proposes 12 multi-object grasps (MOGs) types from a human and robot grasping data set. The grasp types are then analyzed and organized into a MOG taxonomy. This paper first presents three MOG data collection setups: a human finger tracking setup for multi-object grasping demonstrations, a real system with Barretthand, UR5e arm, and a MOG algorithm, a simulation system with the same sett... |
A Novel Convolutional Neural Network for Emotion Recognition Using Neurophysiological Signals | https://ieeexplore.ieee.org/document/9811868/ | [
"Marc Tunnell",
"Huijin Chung",
"Yuchou Chang",
"Marc Tunnell",
"Huijin Chung",
"Yuchou Chang"
] | Non-invasive brain-computer interfaces (BCIs) provide us with the unique ability to classify the psychological state of a person using only neurophysiological signals, such as those captured with an electroencephalogram (EEG). With this ability, new avenues for innovation in the field of healthcare arise, especially as it is used for robotics. EEGNet is a novel deep learning technique for the clas... |
AMI: Adaptive Motion Imitation Algorithm Based on Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9812121/ | [
"Nazita Taghavi",
"Moath H. A. Alqatamin",
"Dan O. Popa",
"Nazita Taghavi",
"Moath H. A. Alqatamin",
"Dan O. Popa"
] | In this paper, we develop a novel adaptive motion imitation algorithm (AMI) for robotic systems. Although AMI can be used in a variety of human-robot interaction scenarios, we are particularly interested in robotic rehabilitation where the robot plays the role of demonstrating and practicing challenging motion physiotherapy. During therapy, the robot first demonstrates a reference trajectory to th... |
Grouptron: Dynamic Multi-Scale Graph Convolutional Networks for Group-Aware Dense Crowd Trajectory Forecasting | https://ieeexplore.ieee.org/document/9811585/ | [
"Rui Zhou",
"Hongyu Zhou",
"Huidong Gao",
"Masayoshi Tomizuka",
"Jiachen Li",
"Zhuo Xu",
"Rui Zhou",
"Hongyu Zhou",
"Huidong Gao",
"Masayoshi Tomizuka",
"Jiachen Li",
"Zhuo Xu"
] | Accurate, long-term forecasting of pedestrian trajectories in highly dynamic and interactive scenes is a longstanding challenge. Recent advances in using data-driven approaches have achieved significant improvements in terms of prediction accuracy. However, the lack of group-aware analysis has limited the performance of forecasting models. This is especially nonnegligible in highly crowded scenes,... |
Deep Learning-driven Front-Following within Close Proximity: a Hands-Free Control Model on a Smart Walker | https://ieeexplore.ieee.org/document/9811910/ | [
"Zhao Chongyu",
"Guo Wenzhi",
"Wen Rongwei",
"Zheng Wang",
"Chuan Wu",
"Zhao Chongyu",
"Guo Wenzhi",
"Wen Rongwei",
"Zheng Wang",
"Chuan Wu"
] | With the ever-increasing elderly population, elder walking assistance is in strong demand. Instead of receiving assistance from a human carer, a smart walker can bring an elder user a more convenient and autonomous walking experience. Towards intelligent and safe walking assistance, we propose a close-proximity front-following model for smart walkers, which analyzes the walking gait and detects th... |
A2DIO: Attention-Driven Deep Inertial Odometry for Pedestrian Localization based on 6D IMU | https://ieeexplore.ieee.org/document/9811714/ | [
"Yingying Wang",
"Hu Cheng",
"Max Q.-H. Meng",
"Yingying Wang",
"Hu Cheng",
"Max Q.-H. Meng"
] | In this work, we propose A2DIO, a novel hybrid neural network model with a set of carefully designed attention mechanisms for pose invariant inertial odometry. The key idea is to extract both local and global features from the window of IMU measurements for velocity prediction. A2DIO leverages the convolutional neural network (CNN) to capture the sectional features and long-short term memory (LSTM... |
Adaptable Action-Aware Vital Models for Personalized Intelligent Patient Monitoring | https://ieeexplore.ieee.org/document/9812176/ | [
"Kai Wu",
"Ee Heng Chen",
"Xing Hao",
"Felix Wirth",
"Keti Vitanova",
"Rüdiger Lange",
"Darius Burschka",
"Kai Wu",
"Ee Heng Chen",
"Xing Hao",
"Felix Wirth",
"Keti Vitanova",
"Rüdiger Lange",
"Darius Burschka"
] | Vital signs such as heart rate, oxygen saturation, and blood pressure are crucial information for healthcare workers to identify clinical deterioration of ward patients. Currently, medical devices monitor these vital signs and trigger alarms when the vital signs are not in the normal ranges based on predefined thresholds, which suggests the presence of clinical deterioration. However, such thresho... |
Human-Following and -guiding in Crowded Environments using Semantic Deep-Reinforcement-Learning for Mobile Service Robots | https://ieeexplore.ieee.org/document/9812111/ | [
"Linh Kästner",
"Bassel Fatloun",
"Zhengcheng Shen",
"Daniel Gawrisch",
"Jens Lambrecht",
"Linh Kästner",
"Bassel Fatloun",
"Zhengcheng Shen",
"Daniel Gawrisch",
"Jens Lambrecht"
] | Assistance robots have gained widespread attention in various industries such as logistics and human assistance. The tasks of guiding or following a human in a crowded environment such as airports or train stations to carry weight or goods is still an open problem. In these use cases, the robot is not only required to intelligently interact with humans, but also to navigate safely among crowds. Th... |
Robust Impedance Control for Dexterous Interaction Using Fractal Impedance Controller with IK-Optimisation | https://ieeexplore.ieee.org/document/9812013/ | [
"Carlo Tiseo",
"Quentin Rouxel",
"Zhibin Li",
"Michael Mistry",
"Carlo Tiseo",
"Quentin Rouxel",
"Zhibin Li",
"Michael Mistry"
] | Robust dynamic interactions are required to move robots in daily environments alongside humans. Optimisation and learning methods have been used to mimic and reproduce human movements. However, they are often not robust and their generalisation is limited. This work proposed a hierarchical control architecture for robot manipulators and provided capabilities of reproducing human-like motions durin... |
Towards Efficient 3D Human Motion Prediction using Deformable Transformer-based Adversarial Network | https://ieeexplore.ieee.org/document/9812325/ | [
"Yu Hua",
"Fan Xuanzhe",
"Hou Yaqing",
"Liu Yi",
"Kang Cai",
"Zhou Dongsheng",
"Zhang Qiang",
"Yu Hua",
"Fan Xuanzhe",
"Hou Yaqing",
"Liu Yi",
"Kang Cai",
"Zhou Dongsheng",
"Zhang Qiang"
] | Human motion prediction is a crucial step for achieving human-robot interactions. While recent transformer-based methods have shown great potentials in 3D human motion prediction, they still suffer from mode collapse to non-plausible poses and quadratically computational complexity with respect to the increasing length of input sequences. In this paper, we propose a novel spatio-temporal deformabl... |
RTGNN: A Novel Approach to Model Stochastic Traffic Dynamics | https://ieeexplore.ieee.org/document/9812104/ | [
"Ke Sun",
"Stephen Chaves",
"Paul Martin",
"Vijay Kumar",
"Ke Sun",
"Stephen Chaves",
"Paul Martin",
"Vijay Kumar"
] | Modeling stochastic traffic dynamics is critical to developing self-driving cars. Because it is difficult to develop first principle models of cars driven by humans, there is great potential for using data driven approaches in developing traffic dynamical models. While there is extensive literature on this subject, previous works mainly address the prediction accuracy of data-driven models. Moreov... |
RMS-FlowNet: Efficient and Robust Multi-Scale Scene Flow Estimation for Large-Scale Point Clouds | https://ieeexplore.ieee.org/document/9811981/ | [
"Ramy Battrawy",
"René Schuster",
"Mohammad–Ali Nikouei Mahani",
"Didier Stricker",
"Ramy Battrawy",
"René Schuster",
"Mohammad–Ali Nikouei Mahani",
"Didier Stricker"
] | The proposed RMS-FlowNet is a novel end-to-end learning-based architecture for accurate and efficient scene flow estimation which can operate on point clouds of high density. For hierarchical scene flow estimation, the existing methods depend on either expensive Farthest-Point-Sampling (FPS) or structure-based scaling which decrease their ability to handle a large number of points. Unlike these me... |
Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras | https://ieeexplore.ieee.org/document/9812137/ | [
"Zhengxia Zou",
"Rusheng Zhang",
"Shengyin Shen",
"Gaurav Pandey",
"Punarjay Chakravarty",
"Armin Parchami",
"Henry X. Liu",
"Zhengxia Zou",
"Rusheng Zhang",
"Shengyin Shen",
"Gaurav Pandey",
"Punarjay Chakravarty",
"Armin Parchami",
"Henry X. Liu"
] | We propose a novel and pragmatic framework for traffic scene perception with roadside cameras. The proposed framework covers a full-stack of roadside perception pipeline for infrastructure-assisted autonomous driving, including object detection, object localization, object tracking, and multi-camera information fusion. Unlike previous vision-based perception frameworks rely upon depth offset or 3D... |
SafetyNet: Safe Planning for Real-World Self-Driving Vehicles Using Machine-Learned Policies | https://ieeexplore.ieee.org/document/9811576/ | [
"Matt Vitelli",
"Yan Chang",
"Yawei Ye",
"Ana Ferreira",
"Maciej Wołczyk",
"Błażej Osiński",
"Moritz Niendorf",
"Hugo Grimmett",
"Qiangui Huang",
"Ashesh Jain",
"Peter Ondruska",
"Matt Vitelli",
"Yan Chang",
"Yawei Ye",
"Ana Ferreira",
"Maciej Wołczyk",
"Błażej Osiński",
"Moritz Niendorf",
"Hugo Grimmett",
"Qiangui Huang",
"Ashesh Jain",
"Peter Ondruska"
] | In this paper we present the first safe system for full control of self-driving vehicles trained from human demonstrations and deployed in challenging, real-world, urban environments. Current industry-standard solutions use rule-based systems for planning. Although they perform reasonably well in common scenarios, the engineering complexity renders this approach incompatible with human-level perfo... |
Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification | https://ieeexplore.ieee.org/document/9812007/ | [
"Jongmin Yu",
"Junsik Kim",
"Minkyung Kim",
"Hyeontaek Oh",
"Jongmin Yu",
"Junsik Kim",
"Minkyung Kim",
"Hyeontaek Oh"
] | Recently, vehicle re-identification methods based on deep learning constitute remarkable achievement. However, this achievement requires large-scale and well-annotated datasets. In constructing the dataset, assigning globally available identities (Ids) to vehicles captured from a great number of cameras is labour-intensive, because it needs to consider their subtle appearance differences or viewpo... |
Decentralized Ride-sharing of Shared Autonomous Vehicles Using Graph Neural Network-Based Reinforcement Learning | https://ieeexplore.ieee.org/document/9811596/ | [
"Boqi Li",
"Nejib Ammar",
"Prashant Tiwari",
"Huei Peng",
"Boqi Li",
"Nejib Ammar",
"Prashant Tiwari",
"Huei Peng"
] | Ride-sharing has important implications for improving the efficiency of mobility-on-demand systems. However, it remains a challenge due to the complex dynamics between vehicles and requests. This paper presents a decentralized ride-sharing algorithm suitable for shared autonomous vehicles (SAVs) deployment. The ride-sharing problem is formulated as a multi-agent reinforcement learning problem. We ... |
Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors | https://ieeexplore.ieee.org/document/9811704/ | [
"Sandipan Das",
"Navid Mahabadi",
"Addi Djikic",
"Cesar Nassir",
"Saikat Chatterjee",
"Maurice Fallon",
"Sandipan Das",
"Navid Mahabadi",
"Addi Djikic",
"Cesar Nassir",
"Saikat Chatterjee",
"Maurice Fallon"
] | We demonstrate a multi-lidar calibration frame-work for large mobile platforms that jointly calibrate the extrinsic parameters of non-overlapping Field-of-View (FoV) lidar sensors, without the need for any external calibration aid. The method starts by estimating the pose of each lidar in its corresponding sensor frame in between subsequent timestamps. Since the pose estimates from the lidars are ... |
An Adaptable Approach to Learn Realistic Legged Locomotion without Examples | https://ieeexplore.ieee.org/document/9812441/ | [
"Daniel Ordonez-Apraez",
"Antonio Agudo",
"Francesc Moreno-Noguer",
"Mario Martin",
"Daniel Ordonez-Apraez",
"Antonio Agudo",
"Francesc Moreno-Noguer",
"Mario Martin"
] | Learning controllers that reproduce legged locomotion in nature has been a longtime goal in robotics and computer graphics. While yielding promising results, recent approaches are not yet flexible enough to be applicable to legged systems of different morphologies. This is partly because they often rely on precise motion capture references or elaborate learning environments that ensure the natural... |
Foothold Evaluation Criterion for Dynamic Transition Feasibility for Quadruped Robots | https://ieeexplore.ieee.org/document/9812434/ | [
"Luca Clemente",
"Octavio Villarreal",
"Angelo Bratta",
"Michele Focchi",
"Victor Barasuol",
"Giovanni Gerardo Muscolo",
"Claudio Semini",
"Luca Clemente",
"Octavio Villarreal",
"Angelo Bratta",
"Michele Focchi",
"Victor Barasuol",
"Giovanni Gerardo Muscolo",
"Claudio Semini"
] | To traverse complex scenarios reliably a legged robot needs to move its base aided by the ground reaction forces, which can only be generated by the legs that are momentarily in contact with the ground. A proper selection of footholds is crucial for maintaining balance. In this paper, we propose a foothold evaluation criterion that considers the transition feasibility for both linear and angular d... |
A Collision-Free MPC for Whole-Body Dynamic Locomotion and Manipulation | https://ieeexplore.ieee.org/document/9812280/ | [
"Jia-Ruei Chiu",
"Jean-Pierre Sleiman",
"Mayank Mittal",
"Farbod Farshidian",
"Marco Hutter",
"Jia-Ruei Chiu",
"Jean-Pierre Sleiman",
"Mayank Mittal",
"Farbod Farshidian",
"Marco Hutter"
] | In this paper, we present a real-time whole-body planner for collision-free legged mobile manipulation. We enforce both self-collision and environment-collision avoidance as soft constraints within a Model Predictive Control (MPC) scheme that solves a multi-contact optimal control problem. By penalizing the signed distances among a set of representative primitive collision bodies, the robot is abl... |
QuadRunner: A Transformable Quasi-Wheel Quadruped | https://ieeexplore.ieee.org/document/9811839/ | [
"Alper Yeldan",
"Abhimanyu Arora",
"Gim Song Soh",
"Alper Yeldan",
"Abhimanyu Arora",
"Gim Song Soh"
] | This paper presents QuadRunner, a transformable quasi-wheel legged robot that achieves both quadruped locomotion and wheel locomotion by exploiting a novel semicircular leg-wheel design with a Trotting Wheel gait. We built upon the Stanford Doggo open architecture platform and integrated it with a transformable leg-wheel design to enhance its locomotion capabilities. On its gait control, improveme... |
Monte Carlo Tree Search Gait Planner for Non-Gaited Legged System Control | https://ieeexplore.ieee.org/document/9812421/ | [
"Lorznzo Amatucci",
"Joon-Ha Kim",
"Jemin Hwangbo",
"Hae-Won Park",
"Lorznzo Amatucci",
"Joon-Ha Kim",
"Jemin Hwangbo",
"Hae-Won Park"
] | In this work, a non-gaited framework for legged system locomotion is presented. The approach decouples the gait sequence optimization by considering the problem as a decision-making process. The redefined contact sequence problem is solved by utilizing a Monte Carlo Tree Search (MCTS) algorithm that exploits optimization-based simulations to evaluate the best search direction. The proposed scheme ... |
Vision-Aided Dynamic Quadrupedal Locomotion on Discrete Terrain Using Motion Libraries | https://ieeexplore.ieee.org/document/9811373/ | [
"Ayush Agrawal",
"Shuxiao Chen",
"Akshara Rai",
"Koushil Sreenath",
"Ayush Agrawal",
"Shuxiao Chen",
"Akshara Rai",
"Koushil Sreenath"
] | In this paper, we present a framework rooted in control and planning that enables quadrupedal robots to traverse challenging terrains with discrete footholds using visual feedback. Navigating discrete terrain is challenging for quadrupeds because the motion of the robot can be aperiodic, highly dynamic, and blind for the hind legs of the robot. Additionally, the robot needs to reason over both the... |
Proactive And Smooth Maneuvering For Navigation Around Pedestrians | https://ieeexplore.ieee.org/document/9812255/ | [
"Maria Kabtoul",
"Anne Spalanzani",
"Philippe Martinet",
"Maria Kabtoul",
"Anne Spalanzani",
"Philippe Martinet"
] | Navigation in close proximity with pedestrians is a challenge on the way to fully automated vehicles. Pedestrian-friendly navigation requires an understanding of pedestrian reaction and intention. Merely safety based reactive systems can lead to sub-optimal navigation solutions resulting in the freezing of the vehicle in many scenarios. Moreover, a strictly reactive method can produce unnatural dr... |
Learning Crowd-Aware Robot Navigation from Challenging Environments via Distributed Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9812011/ | [
"Sango Matsuzaki",
"Yuji Hasegawa",
"Sango Matsuzaki",
"Yuji Hasegawa"
] | This paper presents a deep reinforcement learning (DRL) sframework for safe and efficient navigation in crowded environments. Here, the robot learns cooperative behavior using a new reward function that penalizes robot actions interfering with the pedestrian's movement. Also, we propose a simulated pedestrian policy reflecting data from actual pedestrian movements. Furthermore, we introduce a coll... |
An MPC Framework For Planning Safe & Trustworthy Robot Motions | https://ieeexplore.ieee.org/document/9812160/ | [
"Moritz Eckhoff",
"Robin Jeanne Kirschner",
"Elena Kern",
"Saeed Abdolshah",
"Sami Haddadin",
"Moritz Eckhoff",
"Robin Jeanne Kirschner",
"Elena Kern",
"Saeed Abdolshah",
"Sami Haddadin"
] | Strategies for safe human-robot interaction (HRI), such as the well-established Safe Motion Unit, provide a velocity scaling for biomechanically safe robot motion. In addition, psychologically-based safety approaches are required for trustworthy HRI. Such schemes can be very conservative and robot motion complying with such safety approaches should be time efficient within the robot motion plannin... |
Preemptive Motion Planning for Human-to-Robot Indirect Placement Handovers | https://ieeexplore.ieee.org/document/9811558/ | [
"Andrew Choi",
"Mohammad Khalid Jawed",
"Jungseock Joo",
"Andrew Choi",
"Mohammad Khalid Jawed",
"Jungseock Joo"
] | As technology advances, the need for safe, efficient, and collaborative human-robot-teams has become increasingly important. One of the most fundamental collaborative tasks in any setting is the object handover. Human-to-robot handovers can take either of two approaches: (1) direct hand-to-hand or (2) indirect hand-to-placement-to-pick-up. The latter approach ensures minimal contact between the hu... |
Enhanced Spatial Attention Graph for Motion Planning in Crowded, Partially Observable Environments | https://ieeexplore.ieee.org/document/9812322/ | [
"Weixian Shi",
"Yanying Zhou",
"Xiangyu Zeng",
"Shijie Li",
"Maren Bennewitz",
"Weixian Shi",
"Yanying Zhou",
"Xiangyu Zeng",
"Shijie Li",
"Maren Bennewitz"
] | Collision-free navigation while moving amongst static and dynamic obstacles with a limited sensor range is still a great challenge for modern mobile robots. Therefore, the ability to avoid collisions with obstacles in crowded, partially observable environments is one of the most important indicators to measure the navigation performance of a mobile robot. In this paper, we propose a novel deep rei... |
Balancing Efficiency and Comfort in Robot-Assisted Bite Transfer | https://ieeexplore.ieee.org/document/9812332/ | [
"Suneel Belkhale",
"Ethan K. Gordon",
"Yuxiao Chen",
"Siddhartha Srinivasa",
"Tapomayukh Bhattacharjee",
"Dorsa Sadigh",
"Suneel Belkhale",
"Ethan K. Gordon",
"Yuxiao Chen",
"Siddhartha Srinivasa",
"Tapomayukh Bhattacharjee",
"Dorsa Sadigh"
] | Robot-assisted feeding in household environments is challenging because it requires robots to generate trajectories that effectively bring food items of varying shapes and sizes into the mouth while making sure the user is comfortable. Our key insight is that in order to solve this challenge, robots must balance the efficiency of feeding a food item with the comfort of each individual bite. We for... |
KHAOS: a Kinematic Human Aware Optimization-based System for Reactive Planning of Flying-Coworker | https://ieeexplore.ieee.org/document/9811803/ | [
"Jérôme Truc",
"Phani-Teja Singamaneni",
"Daniel Sidobre",
"Serena Ivaldi",
"Rachid Alami",
"Jérôme Truc",
"Phani-Teja Singamaneni",
"Daniel Sidobre",
"Serena Ivaldi",
"Rachid Alami"
] | The use of drones in human-populated areas is increasing day by day. Such robots flying in close proximity to humans and potentially interacting with them, as in object handover or delivery, need to carefully plan their navigation considering the presence of humans. We propose a humanaware 3D reactive planner based on stochastic optimization for drone navigation. Besides considering the kinematics... |
Joint Communication and Motion Planning for Cobots | https://ieeexplore.ieee.org/document/9812261/ | [
"Mehdi Dadvar",
"Keyvan Majd",
"Elena Oikonomou",
"Georgios Fainekos",
"Siddharth Srivastava",
"Mehdi Dadvar",
"Keyvan Majd",
"Elena Oikonomou",
"Georgios Fainekos",
"Siddharth Srivastava"
] | The increasing deployment of robots in co-working scenarios with humans has revealed complex safety and efficiency challenges in the computation of the robot behavior. Movement among humans is one of the most fundamental —and yet critical—problems in this frontier. While several approaches have addressed this problem from a purely navigational point of view, the absence of a unified paradigm for c... |
A physics-informed, vision-based method to reconstruct all deformation modes in slender bodies | https://ieeexplore.ieee.org/document/9811909/ | [
"Seung Hyun Kim",
"Heng-Sheng Chang",
"Chia-Hsien Shih",
"Naveen Kumar Uppalapati",
"Udit Halder",
"Girish Krishnan",
"Prashant G. Mehta",
"Mattia Gazzola",
"Seung Hyun Kim",
"Heng-Sheng Chang",
"Chia-Hsien Shih",
"Naveen Kumar Uppalapati",
"Udit Halder",
"Girish Krishnan",
"Prashant G. Mehta",
"Mattia Gazzola"
] | This paper is concerned with the problem of estimating (interpolating and smoothing) the shape (pose and the six modes of deformation) of a slender flexible body from multiple camera measurements. This problem is important in both biology, where slender, soft, and elastic structures are ubiquitously encountered across species, and in engineering, particularly in the area of soft robotics. The prop... |
Leveraging distributed contact force measurements for slip detection: a physics-based approach enabled by a data-driven tactile sensor | https://ieeexplore.ieee.org/document/9812186/ | [
"Pietro Griffa",
"Carmelo Sferrazza",
"Raffaello D'Andrea",
"Pietro Griffa",
"Carmelo Sferrazza",
"Raffaello D'Andrea"
] | Grasping objects whose physical properties are unknown is still a great challenge in robotics. Most solutions rely entirely on visual data to plan the best grasping strategy. However, to match human abilities and be able to reliably pick and hold unknown objects, the integration of an artificial sense of touch in robotic systems is pivotal. This paper describes a novel model-based slip detection p... |
Learning to Synthesize Volumetric Meshes from Vision-based Tactile Imprints | https://ieeexplore.ieee.org/document/9812092/ | [
"Xinghao Zhu",
"Siddarth Jain",
"Masayoshi Tomizuka",
"Jeroen Van Baar",
"Xinghao Zhu",
"Siddarth Jain",
"Masayoshi Tomizuka",
"Jeroen Van Baar"
] | Vision-based tactile sensors typically utilize a deformable elastomer and a camera mounted above to provide high-resolution image observations of contacts. Obtaining accurate volumetric meshes for the deformed elastomer can provide direct contact information and benefit robotic grasping and manipulation. This paper focuses on learning to synthesize the volumetric mesh of the elastomer based on the... |
Computation of Dynamic Joint Reaction Forces of PKM and its Use for Load-Minimizing Trajectory Planning | https://ieeexplore.ieee.org/document/9812095/ | [
"D. Gnad",
"H. Gattringer",
"A. Müller",
"W. Höbarth",
"R. Riepl",
"L. Messner",
"D. Gnad",
"H. Gattringer",
"A. Müller",
"W. Höbarth",
"R. Riepl",
"L. Messner"
] | Parallel kinematics machines (PKM) operate with maximal acceleration being designed for highly dynamic manipulation tasks. This leads to extreme loads of the joints, which is usually not accounted for in the motion planning. In this paper an extended inverse dynamics method is introduced, which allows computing the joint reaction forces along with the actuation torques, and provides a basis for ti... |
Toward Physical Human-Robot Interaction Control with Aerial Manipulators: Compliance, Redundancy Resolution, and Input Limits | https://ieeexplore.ieee.org/document/9812451/ | [
"Amr Afifi",
"Mark van Holland",
"Antonio Franchi",
"Amr Afifi",
"Mark van Holland",
"Antonio Franchi"
] | In this paper we introduce a comprehensive framework to control an aerial manipulator, i.e., an aerial vehicle with a robotic arm, in physical interaction with a human operator or co-worker. The framework uses an admittance control paradigm in order to attain human ergonomy and safety; an interaction supervisor to automatically shape the compliance based on the interaction regions defined around t... |
Dynamic Modeling and Digital Twin of a Harmonic Drive Based Collaborative Robot Joint | https://ieeexplore.ieee.org/document/9812458/ | [
"Xingyu Yang",
"Dong Qiang",
"Zixuan Chen",
"Hao Wang",
"Zhengxue Zhou",
"Xuping Zhang",
"Xingyu Yang",
"Dong Qiang",
"Zixuan Chen",
"Hao Wang",
"Zhengxue Zhou",
"Xuping Zhang"
] | Collaborative robots are gradually taking over the leading position in automating the production and manufacturing of the SMEs, where the human-robot collaboration is highly emphasized. Therefore, estimating the force and simulating the performance of robots are of great importance. As a newly introduced technology, digital twin, has gained more attentions for simulation, process evaluation, real-... |
Formation-containment tracking and scaling for multiple quadcopters with an application to choke-point navigation | https://ieeexplore.ieee.org/document/9812172/ | [
"Yu-Hsiang Su",
"Alexander Lanzon",
"Yu-Hsiang Su",
"Alexander Lanzon"
] | This paper investigates the cooperative control problem of choke-point navigation for multiple quadcopters when only their subgroup is equipped with obstacle detecting sensors. We define a quadcopter as a leader if it is equipped with an obstacle detecting sensor; otherwise, it is a follower. In addition, we introduce a virtual leader agent to create the group motion. First, we apply the leader-fo... |
Decentralized Model Predictive Control for Equilibrium-based Collaborative UAV Bar Transportation | https://ieeexplore.ieee.org/document/9811726/ | [
"Roberto C. Sundin",
"Pedro Roque",
"Dimos V. Dimarogonas",
"Roberto C. Sundin",
"Pedro Roque",
"Dimos V. Dimarogonas"
] | In this paper we analyze the equilibrium points of a collaborative transportation task, composed of two unmanned aerial vehicles and a payload - in this case, a bar. Moreover, centralized and decentralized linear model predictive controllers are designed, where the nonlinear dynamics are linearized around the equilibrium points previously analyzed. A comparison between the centralized and decentra... |
Stackelberg Strategic Guidance for Heterogeneous Robots Collaboration | https://ieeexplore.ieee.org/document/9811678/ | [
"Yuhan Zhao",
"Baichuan Huang",
"Jingjin Yu",
"Quanyan Zhu",
"Yuhan Zhao",
"Baichuan Huang",
"Jingjin Yu",
"Quanyan Zhu"
] | In this study, we explore the application of game theory, in particular Stackelberg games, to address the issue of effective coordination strategy generation for heterogeneous robots with one-way communication. To that end, focusing on the task of multi-object rearrangement, we develop a theoretical and algorithmic framework that provides strategic guidance for a pair of robot arms, a leader and a... |
Providing Local Resilience to Vulnerable Areas in Robotic Networks | https://ieeexplore.ieee.org/document/9812033/ | [
"Matthew Cavorsi",
"Stephanie Gil",
"Matthew Cavorsi",
"Stephanie Gil"
] | We study how information flows through a multi-robot network in order to better understand how to provide resilience to malicious information. While the notion of global resilience is well studied, one way existing methods provide global resilience is by bringing robots closer together to improve the connectivity of the network. However, large changes in network structure can impede the team from ... |
Secure Multi-Robot Information Sampling with Periodic and Opportunistic Connectivity | https://ieeexplore.ieee.org/document/9812211/ | [
"Tamim Samman",
"Ayan Dutta",
"O. Patrick Kreidl",
"Swapnoneel Roy",
"Ladislau Bölöni",
"Tamim Samman",
"Ayan Dutta",
"O. Patrick Kreidl",
"Swapnoneel Roy",
"Ladislau Bölöni"
] | Multi-robot teams are becoming an increasingly popular approach for information gathering in large geographic areas, with applications in precision agriculture, surveying the aftermath of natural disasters or tracking pollution. These robot teams are often assembled from untrusted devices not owned by the user, making the maintenance of the integrity of the collected samples an important challenge... |
Driving Swarm: A Swarm Robotics Framework for Intelligent Navigation in a Self-organized World | https://ieeexplore.ieee.org/document/9811852/ | [
"Sebastian Mai",
"Nele Traichel",
"Sanaz Mostaghim",
"Sebastian Mai",
"Nele Traichel",
"Sanaz Mostaghim"
] | Implementing and conducting reproducible experiments on multi-robot hardware platforms are challenging tasks due to variations in hardware, software, and most importantly the intensive implementation effort. In this paper, we aim to present the Driving Swarm software framework which is developed to facilitate the implementation, deployment, supervision, and analysis of multi-robot experiments. We ... |
Dynamic Robot Chain Networks for Swarm Foraging | https://ieeexplore.ieee.org/document/9811625/ | [
"Dohee Lee",
"Qi Lu",
"Tsz-Chiu Au",
"Dohee Lee",
"Qi Lu",
"Tsz-Chiu Au"
] | The objective of foraging robot swarms is to search for and collect resources in an unknown arena as quickly as possible. To avoid the congestion near the central collection zone, we previously proposed an extension to the multiple-place foraging in which robot chains are deployed dynamically so that foraging robots can deliver to the robot chains instead of the central collection zone. However, a... |
On the Convergence of Multi-robot Constrained Navigation: A Parametric Control Lyapunov Function Approach | https://ieeexplore.ieee.org/document/9811807/ | [
"Bowen Weng",
"Hua Chen",
"Wei Zhang",
"Bowen Weng",
"Hua Chen",
"Wei Zhang"
] | This paper studies the distributed multi-robot constrained navigation problem. While the multi-robot collision avoidance has been extensively studied in the literature with safety being the primary focus, the individual robot's destination convergence is not necessarily guaranteed. In particular, robots may get stuck in the local equilibria or periodic orbits of the multi-robot system, some of whi... |
Distributed Swarm Trajectory Optimization for Formation Flight in Dense Environments | https://ieeexplore.ieee.org/document/9812050/ | [
"Lun Quan",
"Longji Yin",
"Chao Xu",
"Fei Gao",
"Lun Quan",
"Longji Yin",
"Chao Xu",
"Fei Gao"
] | For aerial swarms, navigation in a prescribed formation is widely practiced in various scenarios. However, the associated planning strategies typically lack the capability of avoiding obstacles in cluttered environments. To address this deficiency, we present an optimization-based method that ensures collision-free trajectory generation for formation flight. In this paper, a novel differentiable m... |
Optimizing Camera Placements for Overlapped Coverage with 3D Camera Projections | https://ieeexplore.ieee.org/document/9812042/ | [
"Akshay Malhotra",
"Dhananjay Singh",
"Tushar Dadlani",
"Luis Yoichi Morales",
"Akshay Malhotra",
"Dhananjay Singh",
"Tushar Dadlani",
"Luis Yoichi Morales"
] | This paper proposes a method to compute camera 6 DoF poses to achieve a user defined coverage. The camera placement problem is modeled as a combinatorial optimization where given the maximum number of cameras, a camera set is selected from a larger pool of possible camera poses. We propose to minimize the squared error between the desired and the achieved coverage, and formulate the non-linear cos... |
Star-Convolution for Image-Based 3D Object Detection | https://ieeexplore.ieee.org/document/9811612/ | [
"Yuxuan Liu",
"Zhenhua Xu",
"Ming Liu",
"Yuxuan Liu",
"Zhenhua Xu",
"Ming Liu"
] | 3D object detection with only image inputs is an interesting and important problem in computer vision and autonomous driving. Nowadays, most existing monocular 3D object detection algorithms rely solely on the approximation power of convolutional neural networks to learn a mapping from pixels to 3D predictions without knowing the projection matrix of the camera. To endow the networks with camera p... |
Digital Twin with Integrated Robot-Human/Environment Interaction Dynamics for an Industrial Mobile Manipulator | https://ieeexplore.ieee.org/document/9812004/ | [
"Zhengxue Zhou",
"Xingyu Yang",
"Hao Wang",
"Xuping Zhang",
"Zhengxue Zhou",
"Xingyu Yang",
"Hao Wang",
"Xuping Zhang"
] | To achieve real-time dynamic simulation analysis and optimization design, a dynamic digital twin of a nonholonomic mobile manipulator (one UR5e mounted on an industrial mobile robot MIR 200) has been developed in this paper. First, the digital twin integrated with dynamics of a mobile manipulator is established. The framework of the dynamic digital twin is presented in detail. Then, the dynamic mo... |
Combined Grid and Feature-based Mapping of Metal Structures with Ultrasonic Guided Waves | https://ieeexplore.ieee.org/document/9811581/ | [
"Othmane-Latif Ouabi",
"Ayoub Ridani",
"Pascal Pomarede",
"Neil Zeghidour",
"Nico F. Declercq",
"Matthieu Geist",
"Cédric Pradalier",
"Othmane-Latif Ouabi",
"Ayoub Ridani",
"Pascal Pomarede",
"Neil Zeghidour",
"Nico F. Declercq",
"Matthieu Geist",
"Cédric Pradalier"
] | The ultrasonic mapping of plate-based facilities is an essential step towards the robotic inspection of large metal structures such as storage tanks or ship hulls. This work proposes a novel framework that exploits ultrasonic echoes to recover grid-based and feature-based spatial representations jointly. We aim to improve on a previous mapping method [1] subject to errors due to interference, and ... |
Striking the Right Balance: Recall Loss for Semantic Segmentation | https://ieeexplore.ieee.org/document/9811702/ | [
"Junjiao Tian",
"Niluthpol Chowdhury Mithun",
"Zachary Seymour",
"Han-Pang Chiu",
"Zsolt Kira",
"Junjiao Tian",
"Niluthpol Chowdhury Mithun",
"Zachary Seymour",
"Han-Pang Chiu",
"Zsolt Kira"
] | Class imbalance is a fundamental problem in computer vision applications such as semantic segmentation. Specifically, uneven class distributions in a training dataset often result in unsatisfactory performance on under-represented classes. Many works have proposed to weight the standard cross entropy loss function with pre-computed weights based on class statistics, such as the number of samples a... |
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection in Self-Driving Cars | https://ieeexplore.ieee.org/document/9811722/ | [
"Yurong You",
"Carlos Andres Diaz-Ruiz",
"Yan Wang",
"Wei-Lun Chao",
"Bharath Hariharan",
"Mark Campbell",
"Kilian Q Weinberger",
"Yurong You",
"Carlos Andres Diaz-Ruiz",
"Yan Wang",
"Wei-Lun Chao",
"Bharath Hariharan",
"Mark Campbell",
"Kilian Q Weinberger"
] | Self-driving cars must detect other traffic participants like vehicles and pedestrians in 3D in order to plan safe routes and avoid collisions. State-of-the-art 3D object detectors, based on deep learning, have shown promising accuracy but are prone to over-fit domain idiosyncrasies, making them fail in new environments-a serious problem for the robustness of self-driving cars. In this paper, we p... |
Dilated Continuous Random Field for Semantic Segmentation | https://ieeexplore.ieee.org/document/9812064/ | [
"Xi Mo",
"Xiangyu Chen",
"Cuncong Zhong",
"Rui Li",
"Kaidong Li",
"Usman Sajid",
"Xi Mo",
"Xiangyu Chen",
"Cuncong Zhong",
"Rui Li",
"Kaidong Li",
"Usman Sajid"
] | Mean field approximation methodology has laid the foundation of modern Continuous Random Field (CRF) based solutions for the refinement of semantic segmentation. In this paper, we propose to relax the hard constraint of mean field approximation - minimizing the energy term of each node from probabilistic graphical model, by a global optimization with the proposed dilated sparse convolution module ... |
Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling | https://ieeexplore.ieee.org/document/9811646/ | [
"Seunghyeok Back",
"Joosoon Lee",
"Taewon Kim",
"Sangjun Noh",
"Raeyoung Kang",
"Seongho Bak",
"Kyoobin Lee",
"Seunghyeok Back",
"Joosoon Lee",
"Taewon Kim",
"Sangjun Noh",
"Raeyoung Kang",
"Seongho Bak",
"Kyoobin Lee"
] | Instance-aware segmentation of unseen objects is essential for a robotic system in an unstructured environment. Although previous works achieved encouraging results, they were limited to segmenting the only visible regions of unseen objects. For robotic manipulation in a cluttered scene, amodal perception is required to handle the occluded objects behind others. This paper addresses Unseen Object ... |
Rethinking LiDAR Object Detection in adverse weather conditions | https://ieeexplore.ieee.org/document/9812039/ | [
"Teja Vattem",
"George Sebastian",
"Luka Lukic",
"Teja Vattem",
"George Sebastian",
"Luka Lukic"
] | LiDAR sensors are becoming crucial for achieving higher levels of autonomy. With the current sensor technology, LiDAR sensors are still susceptible to erroneous measurements in adverse weather conditions due to weather artifacts observed in the point cloud data. In this work, we analyze the performance of deep learning LiDAR object detectors in adverse weather conditions. We study the under-resear... |
WeakLabel3D-Net: A Complete Framework for Real-Scene LiDAR Point Clouds Weakly Supervised Multi-Tasks Understanding | https://ieeexplore.ieee.org/document/9811959/ | [
"Kangcheng Liu",
"Yuzhi Zhao",
"Zhi Gao",
"Ben M. Chen",
"Kangcheng Liu",
"Yuzhi Zhao",
"Zhi Gao",
"Ben M. Chen"
] | Existing state-of-the-art 3D point clouds understanding methods only perform well in a fully supervised manner. To the best of our knowledge, there exists no unified framework which simultaneously solves the downstream high-level understanding tasks, especially when labels are extremely limited. This work presents a general and simple framework to tackle point clouds understanding when labels are ... |
Multi-Class 3D Object Detection with Single-Class Supervision | https://ieeexplore.ieee.org/document/9812282/ | [
"Mao Ye",
"Chenxi Liu",
"Maoqing Yao",
"Weiyue Wang",
"Zhaoqi Leng",
"Charles R. Qi",
"Dragomir Anguelov",
"Mao Ye",
"Chenxi Liu",
"Maoqing Yao",
"Weiyue Wang",
"Zhaoqi Leng",
"Charles R. Qi",
"Dragomir Anguelov"
] | While multi-class 3D detectors are needed in many robotics applications, training them with fully labeled datasets can be expensive in labeling cost. An alternative approach is to have targeted single-class labels on disjoint data samples. In this paper, we are interested in training a multi-class 3D object detection model, while using these single-class labeled data. We begin by detailing the uni... |
Abstract Flow for Temporal Semantic Segmentation on the Permutohedral Lattice | https://ieeexplore.ieee.org/document/9811818/ | [
"Peer Schutt",
"Radu Alexandru Rosu",
"Sven Behnke",
"Peer Schutt",
"Radu Alexandru Rosu",
"Sven Behnke"
] | Semantic segmentation is a core ability required by autonomous agents, as being able to distinguish which parts of the scene belong to which object class is crucial for navigation and interaction with the environment. Approaches which use only one time-step of data cannot distinguish between moving objects nor can they benefit from temporal integration. In this work, we extend a backbone LatticeNe... |
A Switchable Rigid-Continuum Robot Arm: Design and Testing | https://ieeexplore.ieee.org/document/9812074/ | [
"Hao Wang",
"Zhengxue Zhou",
"Xingyu Yang",
"Xuping Zhang",
"Hao Wang",
"Zhengxue Zhou",
"Xingyu Yang",
"Xuping Zhang"
] | This paper presents a novel robot arm that is capable of switching between a rigid robot arm and a continuum robot arm. Therefore, the novel robot arm can perform adaptive physical interaction and manipulation against complex working environments and tasks. The switch-ability of the robot arm is achieved with two types of joints: knee-like flexible joints and continuum flexible joints, with which ... |
Sen-Glove: A Lightweight Wearable Glove for Hand Assistance with Soft Joint Sensing | https://ieeexplore.ieee.org/document/9812412/ | [
"Linan Deng",
"Yi Shen",
"Yang Hong",
"Yunlong Dong",
"Xin He",
"Ye Yuan",
"Zhi Li",
"Han Ding",
"Linan Deng",
"Yi Shen",
"Yang Hong",
"Yunlong Dong",
"Xin He",
"Ye Yuan",
"Zhi Li",
"Han Ding"
] | Perception and portability are critical issues for wearable gloves in hand assistive engineering. However, available wearable gloves either lack flexible sensing or are bulky. In this paper, we present a tendon-driven lightweight wearable glove with soft joint sensing, Sen-Glove. Sen-Glove is equipped with 14 soft strain sensors, which enables full bending motion monitoring of 14 joints of five fi... |
Compensating for Material Deformation in Foldable Robots via Deep Learning ― A Case Study | https://ieeexplore.ieee.org/document/9811752/ | [
"Mohammad Sharifzadeh",
"Yuhao Jiang",
"Amir Salimi Lafmejani",
"Daniel M. Aukes",
"Mohammad Sharifzadeh",
"Yuhao Jiang",
"Amir Salimi Lafmejani",
"Daniel M. Aukes"
] | Foldable, origami-inspired, and laminate mechanisms are highly susceptible to deformation under external loading, which can lead to position or orientation errors if idealized kinematic models are used. According to dimensional scaling laws, laminate devices can often be treated as rigid bodies at millimeter and smaller scale deformations. However, foldable mechanisms enter the territory of soft r... |
Scalable Simulation and Demonstration of Jumping Piezoelectric 2-D Soft Robots | https://ieeexplore.ieee.org/document/9811927/ | [
"Zhiwu Zheng",
"Prakhar Kumar",
"Yenan Chen",
"Hsin Cheng",
"Sigurd Wagner",
"Minjie Chen",
"Naveen Verma",
"James C. Sturm",
"Zhiwu Zheng",
"Prakhar Kumar",
"Yenan Chen",
"Hsin Cheng",
"Sigurd Wagner",
"Minjie Chen",
"Naveen Verma",
"James C. Sturm"
] | Soft robots have drawn great interest due to their ability to take on a rich range of shapes and motions, compared to traditional rigid robots. However, the motions, and underlying statics and dynamics, pose significant challenges to forming well-generalized and robust models necessary for robot design and control. In this work, we demonstrate a five-actuator soft robot capable of complex motions ... |
Simulation and Fabrication of Soft Robots with Embedded Skeletons | https://ieeexplore.ieee.org/document/9811844/ | [
"James M. Bern",
"Fatemeh Zargarbashi",
"Annan Zhang",
"Josie Hughes",
"Daniela Rus",
"James M. Bern",
"Fatemeh Zargarbashi",
"Annan Zhang",
"Josie Hughes",
"Daniela Rus"
] | Soft robots can be incredibly robust and safe but typically fail to match the strength and precision of rigid robots. This dichotomy between soft and rigid is recently starting to break down, with emerging research interest in hybrid soft-rigid robots. In this work, we draw inspiration from Nature, which achieves the best of both worlds by coupling soft and rigid tissues-like muscle and bone-to pr... |
Reproduction of Human Demonstrations with a Soft-Robotic Arm based on a Library of Learned Probabilistic Movement Primitives | https://ieeexplore.ieee.org/document/9811627/ | [
"Paris Oikonomou",
"Athanasios Dometios",
"Mehdi Khamassi",
"Costas S. Tzafestas",
"Paris Oikonomou",
"Athanasios Dometios",
"Mehdi Khamassi",
"Costas S. Tzafestas"
] | In this paper we introduce a novel technique that aims to control a two-module bio-inspired soft-robotic arm in order to qualitatively reproduce human demonstrations. The main idea behind the proposed methodology is based on the assumption that a complex trajectory can be derived from the composition and asynchronous activation of learned parameterizable simple movements constituting a knowledge b... |
Trajectory Scaling for Reactive Motion Planning | https://ieeexplore.ieee.org/document/9811657/ | [
"Albin Dahlin",
"Yiannis Karayiannidis",
"Albin Dahlin",
"Yiannis Karayiannidis"
] | Trajectory scaling has long been used to address velocity and acceleration constraints in robotic motion planning. In later years, reactive motion planning based on dynamical systems has become popular. The traditional scaling techniques are not always suitable to adopt directly when online modifications of the trajectories are made leading to feasibility problems. In this paper, we propose an app... |
Optimizing Trajectories with Closed-Loop Dynamic SQP | https://ieeexplore.ieee.org/document/9811562/ | [
"Sumeet Singh",
"Jean-Jacques Slotine",
"Vikas Sindhwani",
"Sumeet Singh",
"Jean-Jacques Slotine",
"Vikas Sindhwani"
] | Indirect trajectory optimization methods such as Differential Dynamic Programming (DDP) have found considerable success when only planning under dynamic feasibility constraints. Meanwhile, nonlinear programming (NLP) has been the state-of-the-art approach when faced with additional constraints (e.g., control bounds, obstacle avoidance). However, a naïve implementation of NLP algorithms, e.g., shoo... |
GOMP-FIT: Grasp-Optimized Motion Planning for Fast Inertial Transport | https://ieeexplore.ieee.org/document/9812387/ | [
"Jeffrey Ichnowski",
"Yahav Avigal",
"Yi Liu",
"Ken Goldberg",
"Jeffrey Ichnowski",
"Yahav Avigal",
"Yi Liu",
"Ken Goldberg"
] | High-speed motions in pick-and-place operations are critical to making robots cost-effective in many automation scenarios, from warehouses and manufacturing to hospitals and homes. However, motions can be too fast-such as when the object being transported has an open-top, is fragile, or both. One way to avoid spills or damage, is to move the arm slowly. We propose an alternative: Grasp-Optimized M... |
A Simple Formulation for Fast Prioritized Optimal Control of Robots using Weighted Exact Penalty Functions | https://ieeexplore.ieee.org/document/9812224/ | [
"Ajay Suresha Sathya",
"Wilm Decre",
"Goele Pipeleers",
"Jan Swevers",
"Ajay Suresha Sathya",
"Wilm Decre",
"Goele Pipeleers",
"Jan Swevers"
] | Prioritization of tasks is a common approach to resolve conflicts in instantaneous control of redundant robots. However, the idea of prioritization has not yet been satisfactorily extended to model predictive control (MPC) to allow for real-time robot control. The standard sequential approach for prioritization is unsuitable because of the computational burden involved in solving a nonlinear probl... |
Informative Planning in the Presence of Outliers | https://ieeexplore.ieee.org/document/9812267/ | [
"Weizhe Chen",
"Lantao Liu",
"Weizhe Chen",
"Lantao Liu"
] | Informative planning seeks a sequence of actions that guide the robot to collect the most informative data to build a large-scale environmental model or learn a dynamical system. Existing work in informative planning mainly focuses on proposing new planners and applying them to various robotic applications such as environmental monitoring, autonomous exploration, and system identification. The inf... |
Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires | https://ieeexplore.ieee.org/document/9811559/ | [
"Bryan Lim",
"Luca Grillotti",
"Lorenzo Bernasconi",
"Antoine Cully",
"Bryan Lim",
"Luca Grillotti",
"Lorenzo Bernasconi",
"Antoine Cully"
] | Quality-Diversity (QD) algorithms are powerful exploration algorithms that allow robots to discover large repertoires of diverse and high-performing skills. However, QD algorithms are sample inefficient and require millions of evaluations. In this paper, we propose Dynamics-Aware Quality-Diversity (DA-QD), a framework to improve the sample efficiency of QD algorithms through the use of dynamics mo... |
Contact-Rich Manipulation of a Flexible Object based on Deep Predictive Learning using Vision and Tactility | https://ieeexplore.ieee.org/document/9811940/ | [
"Hideyuki Ichiwara",
"Hiroshi Ito",
"Kenjiro Yamamoto",
"Hiroki Mori",
"Tetsuya Ogata",
"Hideyuki Ichiwara",
"Hiroshi Ito",
"Kenjiro Yamamoto",
"Hiroki Mori",
"Tetsuya Ogata"
] | We achieved contact-rich flexible object manipulation, which was difficult to control with vision alone. In the unzipping task we chose as a validation task, the gripper grasps the puller, which hides the bag state such as the direction and amount of deformation behind it, making it difficult to obtain information to perform the task by vision alone. Additionally, the flexible fabric bag state con... |
Model-based State Estimation of Two-Wheelers | https://ieeexplore.ieee.org/document/9811758/ | [
"Florian Wirth",
"Julian Wadephul",
"Alexander Scheid",
"Carlos Fernandez-Lopez",
"Christoph Stiller",
"Florian Wirth",
"Julian Wadephul",
"Alexander Scheid",
"Carlos Fernandez-Lopez",
"Christoph Stiller"
] | Comprehensive and correct state estimation with meaningful uncertainties is the basis of object-based perception for automated mobile platforms. According to fatality statistics, the most endangered group of vulnerable road users are single-track two-wheelers (ST2W), consisting mainly of cyclists, motorcyclists, and scooter riders. Due to counter-steering, they need more time to adjust their drivi... |
Free Energy Principle for State and Input Estimation of a Quadcopter Flying in Wind | https://ieeexplore.ieee.org/document/9812415/ | [
"Fred Bos",
"Ajith Anil Meera",
"Dennis Benders",
"Martijn Wisse",
"Fred Bos",
"Ajith Anil Meera",
"Dennis Benders",
"Martijn Wisse"
] | The free energy principle from neuroscience provides a brain-inspired perception scheme through a data-driven model learning algorithm called Dynamic Expectation Maximization (DEM). This paper aims at introducing an exper-imental design to provide the first experimental confirmation of the usefulness of DEM as a state and input estimator for real robots. Through a series of quadcopter flight exper... |
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