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Soft-Skin Actuator Capable of Seawater Propulsion based on MagnetoHydroDynamics | https://ieeexplore.ieee.org/document/9981745/ | [
"Mutsuki Matsumoto",
"Yu Kuwajima",
"Hiroki Shigemune",
"Mutsuki Matsumoto",
"Yu Kuwajima",
"Hiroki Shigemune"
] | Underwater robots have a variety of potential uses, including marine resource research, ecological research, and disaster relief. Most of the underwater robots currently in practical use have screw propulsion systems, which have several noises, collision, and entrainment problems. There is a lot of research on underwater robots using soft actuators to solve these problems. However, current soft ac... |
Collaborative Navigation-Aware Coverage in Feature-Poor Environments | https://ieeexplore.ieee.org/document/9981547/ | [
"Özer Özkahraman",
"Petter Ögren",
"Özer Özkahraman",
"Petter Ögren"
] | Multi agent coverage and robot navigation are two very important research fields within robotics. However, their intersection has received limited attention. In multi agent coverage, perfect navigation is often assumed, and in robot navigation, the focus is often to minimize the localization error with the aid of stationary features from the environment. The need for integration of the two becomes... |
Polynomial Time Near-Time-Optimal Multi-Robot Path Planning in Three Dimensions with Applications to Large-Scale UAV Coordination | https://ieeexplore.ieee.org/document/9982231/ | [
"Teng Guo",
"Si Wei Feng",
"Jingjin Yu",
"Teng Guo",
"Si Wei Feng",
"Jingjin Yu"
] | For enabling efficient, large-scale coordination of unmanned aerial vehicles (UAV s) under the labeled setting, in this work, we develop the first polynomial time algorithm for the reconfiguration of many moving bodies in three-dimensional spaces, with provable 1. $x$ asymptotic makespan optimality guarantee under high robot density. More precisely, on an $m_{1} \times m_{2} \times m_{3}$ grid, $m... |
Energy-efficient Orienteering Problem in the Presence of Ocean Currents | https://ieeexplore.ieee.org/document/9981818/ | [
"Ariella Mansfield",
"Douglas G. Macharet",
"M. Ani Hsieh",
"Ariella Mansfield",
"Douglas G. Macharet",
"M. Ani Hsieh"
] | In many environmental monitoring applications robots are often tasked to visit various distinct locations to make observations and/or collect specific measurements. The problem of scheduling and assigning robots to the various tasks and planning feasible paths for the robots can be posed as an Orienteering Problem (OP). In the standard OP, routing and scheduling is achieved by maximizing an object... |
MAPFASTER: A Faster and Simpler take on Multi-Agent Path Finding Algorithm Selection | https://ieeexplore.ieee.org/document/9981981/ | [
"Jean-Marc Alkazzi",
"Anthony Rizk",
"Michel Salomon",
"Abdallah Makhoul",
"Jean-Marc Alkazzi",
"Anthony Rizk",
"Michel Salomon",
"Abdallah Makhoul"
] | Portfolio-based algorithm selection can help in choosing the best suited algorithm for a given task while leveraging the complementary strengths of the candidates. Solving the Multi-Agent Path Finding (MAPF) problem optimally has been proven to be NP-Hard. Furthermore, no single optimal algorithm has been shown to have the fastest runtime for all MAPF problem instances, and there are no proven app... |
Scalable Online Coverage Path Planning for Multi-Robot Systems | https://ieeexplore.ieee.org/document/9981213/ | [
"Ratijit Mitra",
"Indranil Saha",
"Ratijit Mitra",
"Indranil Saha"
] | Online coverage path planning to explore an unknown workspace with multiple homogeneous robots could be either centralized or distributed. While distributed planners are computationally faster, centralized planners can produce more efficient paths, reducing the duration of completing a coverage mission significantly. To exploit the power of a centralized framework, we propose a receding horizon ce... |
DiMOpt: a Distributed Multi-robot Trajectory Optimization Algorithm | https://ieeexplore.ieee.org/document/9981345/ | [
"João Salvado",
"Masoumeh Mansouri",
"Federico Pecora",
"João Salvado",
"Masoumeh Mansouri",
"Federico Pecora"
] | This paper deals with Multi-robot Trajectory Planning, that is, the problem of computing trajectories for multiple robots navigating in a shared space while minimizing for control energy. Approaches based on trajectory optimization can solve this problem optimally. However, such methods are hampered by complex robot dynamics and collision constraints that couple robot's decision variables. We prop... |
Non-Submodular Maximization via the Greedy Algorithm and the Effects of Limited Information in Multi-Agent Execution | https://ieeexplore.ieee.org/document/9982070/ | [
"Benjamin Biggs",
"James McMahon",
"Philip Baldoni",
"Daniel J. Stilwell",
"Benjamin Biggs",
"James McMahon",
"Philip Baldoni",
"Daniel J. Stilwell"
] | We provide theoretical bounds on the worst case performance of the greedy algorithm in seeking to maximize a normalized, monotone, but not necessarily submodular ob-jective function under a simple partition matroid constraint. We also provide worst case bounds on the performance of the greedy algorithm in the case that limited information is available at each planning step. We specifically conside... |
Gathering Physical Particles with a Global Magnetic Field Using Reinforcement Learning | https://ieeexplore.ieee.org/document/9982256/ | [
"Matthias Konitzny",
"Yitong Lu",
"Julien Leclerc",
"Sándor P. Fekete",
"Aaron T. Becker",
"Matthias Konitzny",
"Yitong Lu",
"Julien Leclerc",
"Sándor P. Fekete",
"Aaron T. Becker"
] | For biomedical applications in targeted therapy delivery and interventions, a large swarm of micro-scale particles (“agents”) has to be moved through a maze-like environment (“vascular system”) to a target region (“tumor”). Due to limited on-board capabilities, these agents cannot move autonomously; instead, they are controlled by an external global force that acts uniformly on all particles. In t... |
Contrastive Learning for Cross-Domain Open World Recognition | https://ieeexplore.ieee.org/document/9981592/ | [
"Francesco Cappio Borlino",
"Silvia Bucci",
"Tatiana Tommasi",
"Francesco Cappio Borlino",
"Silvia Bucci",
"Tatiana Tommasi"
] | The ability to evolve is fundamental for any valuable autonomous agent whose knowledge cannot remain limited to that injected by the manufacturer. Consider for example a home assistant robot: it should be able to incrementally learn new object categories when requested, but also to recognize the same objects in different environments (rooms) and poses (hand-held/on the floor/above furniture), whil... |
Efficient Multi-Task Learning via Iterated Single-Task Transfer | https://ieeexplore.ieee.org/document/9981244/ | [
"K.R. Zentner",
"Ujjwal Puri",
"Yulun Zhang",
"Ryan Julian",
"Gaurav S. Sukhatme",
"K.R. Zentner",
"Ujjwal Puri",
"Yulun Zhang",
"Ryan Julian",
"Gaurav S. Sukhatme"
] | In order to be effective general purpose machines in real world environments, robots not only will need to adapt their existing manipulation skills to new circumstances, they will need to acquire entirely new skills on-the-fly. One approach to achieving this capability is via Multi-task Reinforcement Learning (MTRL). Most recent work in MTRL trains a single policy to solve all tasks at once. In th... |
Subspace-based Feature Alignment for Unsupervised Domain Adaptation | https://ieeexplore.ieee.org/document/9981324/ | [
"Eojindl Yi",
"Junmo Kim",
"Eojindl Yi",
"Junmo Kim"
] | Autonomous agents need to perceive the world in a robust way, such that the shift in data distribution does not lead to faulty perception results. When agents cannot be trained with abundant data, agents may need to operate on real world environments while trained on simulated data, and suffer from domain shift. This paper proposes an effective and robust unsupervised domain adaptation (UDA) metho... |
Using Simulation Optimization to Improve Zero-shot Policy Transfer of Quadrotors | https://ieeexplore.ieee.org/document/9981229/ | [
"Sven Gronauer",
"Matthias Kissel",
"Luca Sacchetto",
"Mathias Korte",
"Klaus Diepold",
"Sven Gronauer",
"Matthias Kissel",
"Luca Sacchetto",
"Mathias Korte",
"Klaus Diepold"
] | In this work, we propose a data-driven approach to optimize the parameters of a simulation such that control policies can be directly transferred from simulation to a real-world quadrotor. Our neural network-based policies take only onboard sensor data as input and run entirely on the embed-ded hardware. In real-world experiments, we compare low-level Pulse-Width Modulated control with higher-leve... |
Bilateral Knowledge Distillation for Unsupervised Domain Adaptation of Semantic Segmentation | https://ieeexplore.ieee.org/document/9981567/ | [
"Yunnan Wang",
"Jianxun Li",
"Yunnan Wang",
"Jianxun Li"
] | Unsupervised domain adaptation (UDA) aims to learn domain-invariant representations between the labeled source domain and the unlabeled target domain. Existing self- training-based UDA methods use ground truth and pseudo- labels to supervise source data and target data respectively. However, strong supervision in the source domain and pseudo- label noise in the target domain lead to some problems,... |
Self-Supervised Noisy Label Learning for Source-Free Unsupervised Domain Adaptation | https://ieeexplore.ieee.org/document/9981099/ | [
"Weijie Chen",
"Luojun Lin",
"Shicai Yang",
"Di Xie",
"Shiliang Pu",
"Yueting Zhuang",
"Weijie Chen",
"Luojun Lin",
"Shicai Yang",
"Di Xie",
"Shiliang Pu",
"Yueting Zhuang"
] | Domain adaptation is an important property in robot vision, which enables the neural networks pre-trained on source domains to adapt target domains automatically without any annotation efforts. During this process, source data is not always accessible due to the constraints of expensive storage overhead and data privacy protection. Therefore, the source domain pre-trained model is expected to opti... |
Analysis of Randomization Effects on Sim2Real Transfer in Reinforcement Learning for Robotic Manipulation Tasks | https://ieeexplore.ieee.org/document/9981951/ | [
"Josip Josifovski",
"Mohammadhossein Malmir",
"Noah Klarmann",
"Bare Luka Žagar",
"Nicolás Navarro-Guerrero",
"Alois Knoll",
"Josip Josifovski",
"Mohammadhossein Malmir",
"Noah Klarmann",
"Bare Luka Žagar",
"Nicolás Navarro-Guerrero",
"Alois Knoll"
] | Randomization is currently a widely used approach in Sim2Real transfer for data-driven learning algorithms in robotics. Still, most Sim2Real studies report results for a specific randomization technique and often on a highly customized robotic system, making it difficult to evaluate different randomization approaches systematically. To address this problem, we define an easy-to-reproduce experimen... |
Additive Manufacturing for Tissue Engineering Applications in a Temperature-Controlled Environment | https://ieeexplore.ieee.org/document/9981836/ | [
"Wei-Chih Tseng",
"Chao-Yaug Liao",
"Bo-Ren Chen",
"Luc Chassagne",
"Barthélemy Cagneau",
"Wei-Chih Tseng",
"Chao-Yaug Liao",
"Bo-Ren Chen",
"Luc Chassagne",
"Barthélemy Cagneau"
] | In recent years, with the combination of tissue engineering and additive manufacturing technologies, the possibility of fabricating scaffolds with porosity and complex structure has been improved. Since the properties of most biomaterial inks are influenced by temperature and thereby affect the quality of the scaffolds, a controlled printing environment is very important. This study focuses on tem... |
On CAD Informed Adaptive Robotic Assembly | https://ieeexplore.ieee.org/document/9982242/ | [
"Yotto Koga",
"Heather Kerrick",
"Sachin Chitta",
"Yotto Koga",
"Heather Kerrick",
"Sachin Chitta"
] | We introduce a robotic assembly system that streamlines the design-to-make workflow for going from a CAD model of a product assembly to a fully programmed and adaptive assembly process. Our system captures (in the CAD tool) the intent of the assembly process for a specific robotic workcell and generates a recipe of task-level instructions. By integrating visual sensing with deep-learned perception... |
Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery | https://ieeexplore.ieee.org/document/9981784/ | [
"Niklas Funk",
"Svenja Menzenbach",
"Georgia Chalvatzaki",
"Jan Peters",
"Niklas Funk",
"Svenja Menzenbach",
"Georgia Chalvatzaki",
"Jan Peters"
] | Robot assembly discovery (RAD) is a challenging problem that lives at the intersection of resource allocation and motion planning. The goal is to combine a predefined set of objects to form something new while considering task execution with the robot-in-the-loop. In this work, we tackle the problem of building arbitrary, predefined target structures entirely from scratch using a set of Tetris-lik... |
Assembly Planning from Observations under Physical Constraints | https://ieeexplore.ieee.org/document/9981623/ | [
"Thomas Chabal",
"Robin Strudel",
"Etienne Arlaud",
"Jean Ponce",
"Cordelia Schmid",
"Thomas Chabal",
"Robin Strudel",
"Etienne Arlaud",
"Jean Ponce",
"Cordelia Schmid"
] | This paper addresses the problem of copying an unknown assembly of primitives with known shape and appearance using information extracted from a single photograph by an off-the-shelf procedure for object detection and pose estimation. The proposed algorithm uses a simple combination of physical stability constraints, convex optimization and Monte Carlo tree search to plan assemblies as sequences o... |
Coordinated Toolpath Planning for Multi-Extruder Additive Manufacturing | https://ieeexplore.ieee.org/document/9981543/ | [
"Jayant Khatkar",
"Chanyeol Yool",
"Robert Fitch",
"Lee Clemon",
"Ramgopal Mettu",
"Jayant Khatkar",
"Chanyeol Yool",
"Robert Fitch",
"Lee Clemon",
"Ramgopal Mettu"
] | We present a new algorithm for coordinating the motion of multiple extruders to increase throughput in fused filament fabrication (FFF)/fused deposition modeling (FDM) additive manufacturing. Platforms based on FFF are commonly available and advantageous to several industries, but are limited by slow fabrication time and could be could be significantly improved through efficient use of multiple ex... |
A Hierarchical Finite-State Machine-Based Task Allocation Framework for Human-Robot Collaborative Assembly Tasks | https://ieeexplore.ieee.org/document/9981618/ | [
"Ilias El Makrini",
"Mohsen Omidi",
"Fabio Fusaro",
"Edoardo Lamon",
"Arash Ajoudani",
"Bram Vandcrborght",
"Ilias El Makrini",
"Mohsen Omidi",
"Fabio Fusaro",
"Edoardo Lamon",
"Arash Ajoudani",
"Bram Vandcrborght"
] | Work-related musculoskeletal disorders (MSD) are one of the major cause of injuries and absenteeism at work. These lead to important cost in the manufacturing industry. Human-robot collaboration can help decreasing this issue by appropriately distributing the tasks and decreasing the workload of the factory worker. This paper proposes a novel generic task allocation approach based on hierarchical ... |
Flexible and Precision Snap-Fit Peg-in-Hole Assembly Based on Multiple Sensations and Damping Identification | https://ieeexplore.ieee.org/document/9981639/ | [
"Ruikai Liu",
"Xiansheng Yang",
"Ajian Li",
"Yunjiang Lou",
"Ruikai Liu",
"Xiansheng Yang",
"Ajian Li",
"Yunjiang Lou"
] | Snap-fit peg-in-hole assembly widely exists in both industry and daily life, especially for consumer electronics. The buckle mechanism leads to a damping zone inside the port where insertion force needs to be increased. It is much difficult to automate this process by robots, for size and clearance of the components are always small, and the damping buckle should be perceived and distinguished fro... |
A General Method for Autonomous Assembly of Arbitrary Parts in the Presence of Uncertainty | https://ieeexplore.ieee.org/document/9981276/ | [
"Shichen Cao",
"Jing Xiao",
"Shichen Cao",
"Jing Xiao"
] | In this paper, we propose a novel and general method for autonomous robotic assembly of arbitrary and complex-shaped parts in the presence of 6-dimensional uncertainty. When a nominal assembly motion of the robot holding a part is stopped by contact due to uncertainty, our method finds the best estimate for the uncertainty and the contact configuration of the part based on sensed force/torque and ... |
Fast-Replanning Motion Control for Non-Holonomic Vehicles with Aborting A* | https://ieeexplore.ieee.org/document/9981663/ | [
"Marcell Missura",
"Arindam Roychoudhury",
"Maren Bennewitz",
"Marcell Missura",
"Arindam Roychoudhury",
"Maren Bennewitz"
] | Autonomously driving vehicles must be able to navigate in dynamic and unpredictable environments in a collision-free manner. So far, this has only been partially achieved in driverless cars and warehouse installations where marked structures such as roads, lanes, and traffic signs simplify the motion planning and collision avoidance problem. We are presenting a new control approach for car-like ve... |
Collision and Rollover-Free g2 Path Planning for Mobile Manipulation | https://ieeexplore.ieee.org/document/9981151/ | [
"Jiazhi Song",
"Inna Sharf",
"Jiazhi Song",
"Inna Sharf"
] | This paper presents a path planning refinement technique that allows the efficient collision and rollover-free motion planning for mobile manipulator robots working on rough terrain. First, the necessary theoretical background on a mobile manipulator's kinematics and dynamic stability measure is introduced. Then, after the brief introduction of the sampling-based path planning problem, the additio... |
Fast 3D Sparse Topological Skeleton Graph Generation for Mobile Robot Global Planning | https://ieeexplore.ieee.org/document/9981397/ | [
"Xinyi Chen",
"Boyu Zhou",
"Jiarong Lin",
"Yichen Zhang",
"Fu Zhang",
"Shaojie Shen",
"Xinyi Chen",
"Boyu Zhou",
"Jiarong Lin",
"Yichen Zhang",
"Fu Zhang",
"Shaojie Shen"
] | In recent years, mobile robots are becoming ambitious and deployed in large-scale scenarios. Serving as a high-level understanding of environments, a sparse skeleton graph is beneficial for more efficient global planning. Currently, existing solutions for skeleton graph generation suffer from several major limitations, including poor adaptiveness to different map representations, dependency on rob... |
Learning Enabled Fast Planning and Control in Dynamic Environments with Intermittent Information | https://ieeexplore.ieee.org/document/9981508/ | [
"Matthew Cleaveland",
"Esen Yel",
"Yiannis Kantaros",
"Insup Lee",
"Nicola Bezzo",
"Matthew Cleaveland",
"Esen Yel",
"Yiannis Kantaros",
"Insup Lee",
"Nicola Bezzo"
] | This paper addresses a safe planning and control problem for mobile robots operating in communication- and sensor-limited dynamic environments. In this case the robots cannot sense the objects around them and must instead rely on intermittent, external information about the environment, as e.g., in underwater applications. The challenge in this case is that the robots must plan using only this sta... |
NMPC-LBF: Nonlinear MPC with Learned Barrier Function for Decentralized Safe Navigation of Multiple Robots in Unknown Environments | https://ieeexplore.ieee.org/document/9981177/ | [
"Amir Salimi Lafmejani",
"Spring Berman",
"Georgios Fainekos",
"Amir Salimi Lafmejani",
"Spring Berman",
"Georgios Fainekos"
] | In this paper, we present a decentralized control approach based on a Nonlinear Model Predictive Control (NMPC) method that employs barrier certificates for safe navigation of multiple nonholonomic wheeled mobile robots in unknown environments with static and/or dynamic obstacles. This method incorporates a Learned Barrier Function (LBF) into the NMPC design in order to guarantee safe robot naviga... |
T-PRM: Temporal Probabilistic Roadmap for Path Planning in Dynamic Environments | https://ieeexplore.ieee.org/document/9981739/ | [
"Matthias Hüppi",
"Luca Bartolomei",
"Ruben Mascaro",
"Margarita Chli",
"Matthias Hüppi",
"Luca Bartolomei",
"Ruben Mascaro",
"Margarita Chli"
] | Sampling-based motion planners are widely used in robotics due to their simplicity, flexibility and computational efficiency. However, in their most basic form, these algorithms operate under the assumption of static scenes and lack the ability to avoid collisions with dynamic (i.e. moving) obstacles. This raises safety concerns, limiting the range of possible applications of mobile robots in the ... |
Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner | https://ieeexplore.ieee.org/document/9981648/ | [
"Philémon Brakel",
"Steven Bohez",
"Leonard Hasenclever",
"Nicolas Heess",
"Konstantinos Bousmalis",
"Philémon Brakel",
"Steven Bohez",
"Leonard Hasenclever",
"Nicolas Heess",
"Konstantinos Bousmalis"
] | We propose a simple imitation learning procedure for learning locomotion controllers that can walk over very challenging terrains. We use trajectory optimization (TO) to produce a large dataset of trajectories over procedurally generated terrains and use Reinforcement Learning (RL) to imitate these trajectories. We demonstrate with a realistic model of the ANYmal robot that the learned controllers... |
A Versatile Co-Design Approach For Dynamic Legged Robots | https://ieeexplore.ieee.org/document/9981378/ | [
"Traiko Dinev",
"Carlos Mastalli",
"Vladimir Ivan",
"Steve Tonneau",
"Sethu Vijayakumar",
"Traiko Dinev",
"Carlos Mastalli",
"Vladimir Ivan",
"Steve Tonneau",
"Sethu Vijayakumar"
] | We present a versatile framework for the computational co-design of legged robots and dynamic maneuvers. Current state-of-the-art approaches are typically based on random sampling or concurrent optimization. We propose a novel bilevel optimization approach that exploits the derivatives of the motion planning sub-problem (i.e., the lower level). These motion-planning derivatives allow us to incorpo... |
Motion Planning for Agile Legged Locomotion using Failure Margin Constraints | https://ieeexplore.ieee.org/document/9981903/ | [
"Kevin Green",
"John Warila",
"Ross L. Hatton",
"Jonathan Hurst",
"Kevin Green",
"John Warila",
"Ross L. Hatton",
"Jonathan Hurst"
] | The complex dynamics of agile robotic legged locomotion requires motion planning to intelligently adjust footstep locations. Often, bipedal footstep and motion planning use mathematically simple models such as the linear inverted pendulum, instead of dynamically-rich models that do not have closed-form solutions. We propose a real-time optimization method to plan for dynamical models that do not h... |
Robust High-Speed Running for Quadruped Robots via Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9982132/ | [
"Guillaume Bellegarda",
"Yiyu Chen",
"Zhuochen Liu",
"Quan Nguyen",
"Guillaume Bellegarda",
"Yiyu Chen",
"Zhuochen Liu",
"Quan Nguyen"
] | Deep reinforcement learning has emerged as a popular and powerful way to develop locomotion controllers for quadruped robots. Common approaches have largely focused on learning actions directly in joint space, or learning to modify and offset foot positions produced by trajectory generators. Both approaches typically require careful reward shaping and training for millions of time steps, and with ... |
Real-time Digital Double Framework to Predict Collapsible Terrains for Legged Robots | https://ieeexplore.ieee.org/document/9981613/ | [
"Garen Haddeler",
"Hari P. Palanivelu",
"Yung Chuen Ng",
"Fabien Colonnier",
"Albertus H. Adiwahono",
"Zhibin Li",
"Chee-Meng Chew",
"Meng Yee Chuah",
"Garen Haddeler",
"Hari P. Palanivelu",
"Yung Chuen Ng",
"Fabien Colonnier",
"Albertus H. Adiwahono",
"Zhibin Li",
"Chee-Meng Chew",
"Meng Yee Chuah"
] | Inspired by the digital twinning systems, a novel real-time digital double framework is developed to enhance robot perception of the terrain conditions. Based on the very same physical model and motion control, this work exploits the use of such simulated digital double synchronized with a real robot to capture and extract discrepancy information between the two systems, which provides high dimens... |
Towards Learning to Play Piano with Dexterous Hands and Touch | https://ieeexplore.ieee.org/document/9981221/ | [
"Huazhe Xu",
"Yuping Luo",
"Shaoxiong Wang",
"Trevor Darrell",
"Roberto Calandra",
"Huazhe Xu",
"Yuping Luo",
"Shaoxiong Wang",
"Trevor Darrell",
"Roberto Calandra"
] | As Liszt once said “(a virtuoso) must call up scent and blossom, and breathe the breath of life”, a virtuoso plays the piano with passion, poetry, and extraordinary technical ability. Hence, piano playing, being a task that is quintessentially human, becomes a hallmark for roboticians and artificial intelligence researchers to pursue. In this paper, we advocate an end-to-end reinforcement learning... |
Consensus-based Normalizing-Flow Control: A Case Study in Learning Dual-Arm Coordination | https://ieeexplore.ieee.org/document/9981827/ | [
"Hang Yin",
"Christos K. Verginis",
"Danica Kragic",
"Hang Yin",
"Christos K. Verginis",
"Danica Kragic"
] | We develop two consensus-based learning algorithms for multi-robot systems applied on complex tasks involving collision constraints and force interactions, such as the cooperative peg-in-hole placement. The proposed algorithms integrate multi-robot distributed consensus and normalizing-flow-based reinforcement learning. The algorithms guarantee the stability and the consensus of the multi-robot sy... |
Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement | https://ieeexplore.ieee.org/document/9981715/ | [
"Kai Gao",
"Jingjin Yu",
"Kai Gao",
"Jingjin Yu"
] | We investigate the problem of coordinating two robot arms to solve non-monotone tabletop multi-object re- arrangement tasks. In a non-monotone rearrangement task, complex object-object dependencies exist that require moving some objects multiple times to solve an instance. In working with two arms in a large workspace, some objects must be handed off between the robots, which further complicates t... |
Simultaneous Depth Estimation and Localization for Cell Manipulation Based on Deep Learning | https://ieeexplore.ieee.org/document/9982228/ | [
"Zengshuo Wang",
"Huiying Gong",
"Ke Li",
"Bin Yang",
"Yue Du",
"Yaowei Liu",
"Xin Zhao",
"Mingzhu Sun",
"Zengshuo Wang",
"Huiying Gong",
"Ke Li",
"Bin Yang",
"Yue Du",
"Yaowei Liu",
"Xin Zhao",
"Mingzhu Sun"
] | Visual localization, which is a key technology to realize the automation of cell manipulation, has been widely studied. Since the depth of field of the microscope is narrow, the planar localization and depth estimation are usually coupled together. At present, most methods adopt the serial working mode of focusing first and then planar localization, but they usually do not have good real-time perf... |
DUQIM-Net: Probabilistic Object Hierarchy Representation for Multi-View Manipulation | https://ieeexplore.ieee.org/document/9981406/ | [
"Vladimir Tchuiev",
"Yakov Miron",
"Dotan Di Castro",
"Vladimir Tchuiev",
"Yakov Miron",
"Dotan Di Castro"
] | Object manipulation in cluttered scenes is a difficult and important problem in robotics. To efficiently manipulate objects, it is crucial to understand their surroundings, especially in cases where multiple objects are stacked one on top of the other, preventing effective grasping. We here present DUQIM-Net, a decision-making approach for object manipulation in a setting of stacked objects. In DU... |
Downwash-aware Control Allocation for Over-actuated UAV Platforms | https://ieeexplore.ieee.org/document/9981140/ | [
"Yao Su",
"Chi Chu",
"Meng Wang",
"Jiarui Li",
"Liu Yang",
"Yixin Zhu",
"Hangxin Liu",
"Yao Su",
"Chi Chu",
"Meng Wang",
"Jiarui Li",
"Liu Yang",
"Yixin Zhu",
"Hangxin Liu"
] | Tracking position and orientation independently affords more agile maneuver for over-actuated multirotor Unmanned Aerial Vehicles (UAVs) while introducing undesired downwash effects; downwash flows generated by thrust generators may counteract others due to close proximity, which significantly threatens the stability of the platform. The complexity of modeling aerodynamic airflow challenges contro... |
Siamese Object Tracking for Vision-Based UAM Approaching with Pairwise Scale-Channel Attention | https://ieeexplore.ieee.org/document/9982189/ | [
"Guangze Zheng",
"Changhong Fu",
"Junjie Ye",
"Bowen Li",
"Geng Lu",
"Jia Pan",
"Guangze Zheng",
"Changhong Fu",
"Junjie Ye",
"Bowen Li",
"Geng Lu",
"Jia Pan"
] | Although the manipulating of the unmanned aerial manipulator (UAM) has been widely studied, vision-based UAM approaching, which is crucial to the subsequent manipulating, generally lacks effective design. The key to the visual UAM approaching lies in object tracking, while current UAM tracking typically relies on costly model-based methods. Besides, UAM approaching often confronts more severe obje... |
Unsteady aerodynamic modeling of Aerobat using lifting line theory and Wagner's function | https://ieeexplore.ieee.org/document/9982125/ | [
"Eric Sihite",
"Paul Ghanem",
"Adarsh Salagame",
"Alireza Ramezani",
"Eric Sihite",
"Paul Ghanem",
"Adarsh Salagame",
"Alireza Ramezani"
] | Flying animals possess highly complex physical characteristics and are capable of performing agile maneuvers using their wings. The flapping wings generate complex wake structures that influence the aerodynamic forces, which can be difficult to model. While it is possible to model these forces using fluidstructure interaction, it is very computationally expensive and difficult to formulate. In thi... |
Design and Analysis of Truss Aerial Transportation System (TATS): The Lightweight Bar Spherical Joint Mechanism | https://ieeexplore.ieee.org/document/9981191/ | [
"Xiaozhen Zhang",
"Qingkai Yang",
"Rui Yu",
"Delong Wu",
"Shaozhun Wei",
"Jinqiang Cui",
"Hao Fang",
"Xiaozhen Zhang",
"Qingkai Yang",
"Rui Yu",
"Delong Wu",
"Shaozhun Wei",
"Jinqiang Cui",
"Hao Fang"
] | In aerial cooperative transportation missions, it has been recognized that for small-sized but heavy payloads, the cable-suspended framework is a preferred manner. However, to maintain proper safe flight distances, cables always stay inclined, which implies that horizontal force components have to be generated by UAVs, and only partial thrust forces are used for gravity compensation. To overcome t... |
Real-Time Trajectory Planning for Aerial Perching | https://ieeexplore.ieee.org/document/9981489/ | [
"Jialin Ji",
"Tiankai Yang",
"Chao Xu",
"Fei Gao",
"Jialin Ji",
"Tiankai Yang",
"Chao Xu",
"Fei Gao"
] | This paper presents a novel trajectory planning method for aerial perching. Compared with the existing work, the terminal states and the trajectory durations can be adjusted adaptively, instead of being determined in advance. Further-more, our planner is able to minimize the tangential relative speed on the premise of safety and dynamic feasibility. This feature is especially notable on micro aeri... |
Dynamic Free-Space Roadmap for Safe Quadrotor Motion Planning | https://ieeexplore.ieee.org/document/9981447/ | [
"Junlong Guo",
"Zhiren Xun",
"Shuang Geng",
"Yi Lin",
"Chao Xu",
"Fei Gao",
"Junlong Guo",
"Zhiren Xun",
"Shuang Geng",
"Yi Lin",
"Chao Xu",
"Fei Gao"
] | Free-space-oriented roadmaps typically generate a series of convex geometric primitives, which constitute the safe region for motion planning. However, a static environment is assumed for this kind of roadmap. This assumption makes it unable to deal with dynamic obstacles and limits its applications. In this paper, we present a dynamic free-space roadmap, which provides feasible spaces and a navig... |
Obstacle Avoidance of Resilient UAV Swarm Formation with Active Sensing System in the Dense Environment | https://ieeexplore.ieee.org/document/9981858/ | [
"Peng Peng",
"Wei Dong",
"Gang Chen",
"Xiangyang Zhu",
"Peng Peng",
"Wei Dong",
"Gang Chen",
"Xiangyang Zhu"
] | This paper proposes a perception-shared and swarm trajectory global optimal (STGO) algorithm fused UAVs formation motion planning framework aided by an active sensing system. First, the point cloud received by each UAV is fit by the gaussian mixture model (GMM) and transmitted in the swarm. Resampling from the received GMM contributes to a global map, which is used as the foundation for consensus.... |
Autoexplorer: Autonomous Exploration of Unknown Environments using Fast Frontier-Region Detection and Parallel Path Planning | https://ieeexplore.ieee.org/document/9981263/ | [
"Kyung Min Han",
"Young J. Kim",
"Kyung Min Han",
"Young J. Kim"
] | We propose a fully autonomous system for mobile robot exploration in unknown environments. Our system employs a novel frontier detection algorithm based on the fast front propagation (FFP) technique and uses parallel path planning to reach the detected front regions. Given an occupancy grid map in 2D, possibly updated online, our algorithm can find all the frontier points that can allow mobile rob... |
Real-Time Visual Inertial Odometry with a Resource-Efficient Harris Corner Detection Accelerator on FPGA Platform | https://ieeexplore.ieee.org/document/9981598/ | [
"Pengfei Gu",
"Ziyang Meng",
"Pengkun Zhou",
"Pengfei Gu",
"Ziyang Meng",
"Pengkun Zhou"
] | Visual Inertial Odometry (VIO) is a widely studied localization technique in robotics. State-of-the-art VIO algorithms are composed of two parts: a frontend which performs visual perception and inertial measurement pre-processing, and a backend which fuses vision and inertial measurements to estimate the robot's pose. Both image processing in the frontend and sensor fusion in the backend are compu... |
MPNP: Multi-Policy Neural Planner for Urban Driving | https://ieeexplore.ieee.org/document/9982111/ | [
"Jie Cheng",
"Ren Xin",
"Sheng Wang",
"Ming Liu",
"Jie Cheng",
"Ren Xin",
"Sheng Wang",
"Ming Liu"
] | Our goal is to train a neural planner that can capture diverse driving behaviors in complex urban scenarios. We observe that even state-of-the-art neural planners are struggling to perform common maneuvers such as lane change, which is rather natural for human drivers. We propose to explore the multi-modalities in the planning problem and force the neural planner to explicitly consider different p... |
Contextual Tuning of Model Predictive Control for Autonomous Racing | https://ieeexplore.ieee.org/document/9981780/ | [
"Lukas P. Fröhlich",
"Christian Küttel",
"Elena Arcari",
"Lukas Hewing",
"Melanie N. Zeilinger",
"Andrea Carron",
"Lukas P. Fröhlich",
"Christian Küttel",
"Elena Arcari",
"Lukas Hewing",
"Melanie N. Zeilinger",
"Andrea Carron"
] | Learning-based model predictive control has been widely applied in autonomous racing to improve the closed-loop behaviour of vehicles in a data-driven manner. When environmental conditions change, e.g., due to rain, often only the predictive model is adapted, but the controller parameters are kept constant. However, this can lead to suboptimal behaviour. In this paper, we address the problem of da... |
Temporal Logic Path Planning under Localization Uncertainty | https://ieeexplore.ieee.org/document/9981624/ | [
"Amit Dhyani",
"Indranil Saha",
"Amit Dhyani",
"Indranil Saha"
] | We present a method to find the optimal control strategy for a robot using prior information of localization that maximizes the probability of satisfaction of a temporal logic specification while considering the uncertainty in both motion and sensing, two major causes for localization uncertainty. The specifications are given in the probabilistic computation tree logic (PCTL) formulae over a set o... |
Navigating to Objects in Unseen Environments by Distance Prediction | https://ieeexplore.ieee.org/document/9981766/ | [
"Minzhao Zhu",
"Binglei Zhao",
"Tao Kong",
"Minzhao Zhu",
"Binglei Zhao",
"Tao Kong"
] | Object Goal Navigation (ObjectNav) task is to navigate an agent to an object category in unseen environments without a pre-built map. In this paper, we solve this task by predicting the distance to the target using semantically-related objects as cues. Based on the estimated distance to the target object, our method directly choose optimal midterm goals that are more likely to have a shorter path ... |
Depth-CUPRL: Depth-Imaged Contrastive Unsupervised Prioritized Representations in Reinforcement Learning for Mapless Navigation of Unmanned Aerial Vehicles | https://ieeexplore.ieee.org/document/9982161/ | [
"Junior C. de Jesus",
"Victor A. Kich",
"Alisson H. Kolling",
"Ricardo B. Grando",
"Rodrigo S. Guerra",
"Paulo L. J. Drews",
"Junior C. de Jesus",
"Victor A. Kich",
"Alisson H. Kolling",
"Ricardo B. Grando",
"Rodrigo S. Guerra",
"Paulo L. J. Drews"
] | Reinforcement Learning (RL) has presented an impressive performance in video games through raw pixel imaging and continuous control tasks. However, RL performs poorly with high-dimensional observations such as raw pixel images. It is generally accepted that physical state-based RL policies such as laser sensor measurements give a more sample-efficient result than learning by pixels. This work pres... |
DSOL: A Fast Direct Sparse Odometry Scheme | https://ieeexplore.ieee.org/document/9981491/ | [
"Chao Qu",
"Shreyas S. Shivakumar",
"Ian D. Miller",
"Camillo J. Taylor",
"Chao Qu",
"Shreyas S. Shivakumar",
"Ian D. Miller",
"Camillo J. Taylor"
] | In this paper, we describe Direct Sparse Odometry Lite (DSOL), an improved version of Direct Sparse Odometry (DSO) [1]. We propose several algorithmic and implementation enhancements which speed up computation by a significant factor (on average 5x) even on resource-constrained platforms. The increase in speed allows us to process images at higher frame rates, which in turn provides better results... |
Planning for Negotiations in Autonomous Driving using Reinforcement Learning | https://ieeexplore.ieee.org/document/9981988/ | [
"Roi Reshef",
"Roi Reshef"
] | Planning autonomous driving behaviors in dense traffic is challenging. Human drivers are able to influence their road environment to achieve (otherwise unachievable) goals, by communicating their intents to other drivers. An autonomous system that is required to drive in the presence of human traffic must thus possess this fundamental negotiation capability. This work presents a novel benchmark th... |
Towards Specialized Hardware for Learning-based Visual Odometry on the Edge | https://ieeexplore.ieee.org/document/9982046/ | [
"Siyuan Chen",
"Ken Mai",
"Siyuan Chen",
"Ken Mai"
] | Learning-based visual odometry (VO) has gained increasing popularity in autonomous navigation of small robots. However, most methods in the category require computation resources not normally available on edge systems. We contend that specialized hardware accelerators are ideal solutions to this problem because of their superior energy efficiency. In this paper, we first propose a model to derive ... |
MPT-Net: Mask Point Transformer Network for Large Scale Point Cloud Semantic Segmentation | https://ieeexplore.ieee.org/document/9981809/ | [
"Zhe Jun Tang",
"Tat-Jen Cham",
"Zhe Jun Tang",
"Tat-Jen Cham"
] | Point cloud semantic segmentation is important for road scene perception, a task for driverless vehicles to achieve full fledged autonomy. In this work, we introduce Mask Point Transformer Network (MPT-Net), a novel architecture for point cloud segmentation that is simple to implement. MPT-Net consists of a local and global feature encoder and a transformer based decoder; a 3D Point-Voxel Convolut... |
Timestamp-Supervised Action Segmentation with Graph Convolutional Networks | https://ieeexplore.ieee.org/document/9981351/ | [
"Hamza Khan",
"Sanjay Haresh",
"Awais Ahmed",
"Shakeeb Siddiqui",
"Andrey Konin",
"M. Zeeshan Zia",
"Quoc-Huy Tran",
"Hamza Khan",
"Sanjay Haresh",
"Awais Ahmed",
"Shakeeb Siddiqui",
"Andrey Konin",
"M. Zeeshan Zia",
"Quoc-Huy Tran"
] | We introduce a novel approach for temporal activity segmentation with timestamp supervision. Our main contribution is a graph convolutional network, which is learned in an end-to-end manner to exploit both frame features and connections between neighboring frames to generate dense framewise labels from sparse timestamp labels. The gener-ated dense framewise labels can then be used to train the seg... |
CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in Space | https://ieeexplore.ieee.org/document/9981172/ | [
"Shunli Wang",
"Shuaibing Wang",
"Bo Jiao",
"Dingkang Yang",
"Liuzhen Su",
"Peng Zhai",
"Chixiao Chen",
"Lihua Zhang",
"Shunli Wang",
"Shuaibing Wang",
"Bo Jiao",
"Dingkang Yang",
"Liuzhen Su",
"Peng Zhai",
"Chixiao Chen",
"Lihua Zhang"
] | Reliable and stable 6D pose estimation of un-cooperative space objects plays an essential role in on-orbit servicing and debris removal missions. Considering that the pose estimator is sensitive to background interference, this paper proposes a counterfactual analysis framework named CA-SpaceNet to complete robust 6D pose estimation of the space-borne targets under complicated background. Specific... |
3D Object Aided Self-Supervised Monocular Depth Estimation | https://ieeexplore.ieee.org/document/9981590/ | [
"Songlin Wei",
"Guodong Chen",
"Wenzheng Chi",
"Zhenhua Wang",
"Lining Sun",
"Songlin Wei",
"Guodong Chen",
"Wenzheng Chi",
"Zhenhua Wang",
"Lining Sun"
] | Monocular depth estimation has been actively studied in fields such as robot vision, autonomous driving, and 3D scene understanding. Given a sequence of color images, unsupervised learning methods based on the framework of Structure-From-Motion (SfM) simultaneously predict depth and camera relative pose. However, dynamically moving objects in the scene violate the static world assumption, resultin... |
DeepMLE: A Robust Deep Maximum Likelihood Estimator for Two-view Structure from Motion | https://ieeexplore.ieee.org/document/9981975/ | [
"Yuxi Xiao",
"Li Li",
"Xiaodi Li",
"Jian Yao",
"Yuxi Xiao",
"Li Li",
"Xiaodi Li",
"Jian Yao"
] | Two-view structure from motion (SfM) is the cornerstone of 3D reconstruction and visual SLAM (vSLAM). Many existing end-to-end learning-based methods usually formulate it as a brute regression problem. However, the inadequate utilization of traditional geometry model makes the model not robust in unseen environments. To improve the generalization capability and robustness of end-to-end two-view Sf... |
Attention-guided RGB-D Fusion Network for Category-level 6D Object Pose Estimation | https://ieeexplore.ieee.org/document/9981242/ | [
"Hao Wang",
"Weiming Li",
"Jiyeon Kim",
"Qiang Wang",
"Hao Wang",
"Weiming Li",
"Jiyeon Kim",
"Qiang Wang"
] | This work focuses on estimating 6D poses and sizes of category-level objects from a single RGB-D image. How to exploit the complementary RGB and depth features plays an important role in this task yet remains an open question. Due to the large intra-category texture and shape variations, an object instance in test may have different RGB and depth features from those of the object instances in trai... |
Robust Human Motion Forecasting using Transformer-based Model | https://ieeexplore.ieee.org/document/9981877/ | [
"Esteve Valls Mascaro",
"Shuo Ma",
"Hyemin Ahn",
"Dongheui Lee",
"Esteve Valls Mascaro",
"Shuo Ma",
"Hyemin Ahn",
"Dongheui Lee"
] | Comprehending human motion is a fundamental challenge for developing Human-Robot Collaborative applications. Computer vision researchers have addressed this field by only focusing on reducing error in predictions, but not taking into account the requirements to facilitate its implementation in robots. In this paper, we propose a new model based on Transformer that simultaneously deals with the rea... |
Human-Robot Collaborative Carrying of Objects with Unknown Deformation Characteristics | https://ieeexplore.ieee.org/document/9981948/ | [
"Doganay Sirintuna",
"Alberto Giammarino",
"Arash Ajoudani",
"Doganay Sirintuna",
"Alberto Giammarino",
"Arash Ajoudani"
] | In this work, we introduce an adaptive control framework for human-robot collaborative transportation of objects with unknown deformation behaviour. The proposed framework takes as input the haptic information transmitted through the object, and the kinematic information of the human body obtained from a motion capture system to create reactive whole-body motions on a mobile collaborative robot. I... |
The Predictive Kinematic Control Tree: Enhancing Teleoperation of Redundant Robots through Probabilistic User Models | https://ieeexplore.ieee.org/document/9982150/ | [
"Connor Brooks",
"Daniel Szafir",
"Connor Brooks",
"Daniel Szafir"
] | When teleoperating complex robotic manipula-tors, operators often find it most natural to issue commands that dictate end effector movements in task space. If the robot has redundant degrees of freedom, the translation of this com-mand from task space into configuration space can affect the robot's maneuverability, smoothness of motion, and the general precision of the teleoperated system. In this... |
Sociable and Ergonomic Human-Robot Collaboration through Action Recognition and Augmented Hierarchical Quadratic Programming | https://ieeexplore.ieee.org/document/9982160/ | [
"Francesco Tassi",
"Francesco Iodice",
"Elena De Momi",
"Arash Ajoudani",
"Francesco Tassi",
"Francesco Iodice",
"Elena De Momi",
"Arash Ajoudani"
] | The recognition of actions performed by humans and the anticipation of their intentions are important enablers to yield sociable and successful collaboration in human-robot teams. Meanwhile, robots should have the capacity to deal with multiple objectives and constraints, arising from the collaborative task or the human. In this regard, we propose vision techniques to perform human action recognit... |
Bounded Rational Game-theoretical Modeling of Human Joint Actions with Incomplete Information | https://ieeexplore.ieee.org/document/9982108/ | [
"Yiwei Wang",
"Pallavi Shintre",
"Sunny Amatya",
"Wenlong Zhang",
"Yiwei Wang",
"Pallavi Shintre",
"Sunny Amatya",
"Wenlong Zhang"
] | As humans and robots start to collaborate in close proximity, robots are tasked to perceive, comprehend, and anticipate human partners' actions, which demands a predictive model to describe how humans collaborate with each other in joint actions. Previous studies either simplify the collaborative task as an optimal control problem between two agents or do not consider the learning process of human... |
Quantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System | https://ieeexplore.ieee.org/document/9981032/ | [
"Keya Ghonasgi",
"Reuth Mirsky",
"Adrian M. Haith",
"Peter Stone",
"Ashish D. Deshpande",
"Keya Ghonasgi",
"Reuth Mirsky",
"Adrian M. Haith",
"Peter Stone",
"Ashish D. Deshpande"
] | While human-robot interaction studies are becoming more common, quantification of the effects of repeated interaction with an exoskeleton remains unexplored. We draw upon existing literature in human skill assessment and present extrinsic and intrinsic performance metrics that quantify how the human-exoskeleton system's behavior changes over time. Specifically, in this paper, we present a new perf... |
Transporters with Visual Foresight for Solving Unseen Rearrangement Tasks | https://ieeexplore.ieee.org/document/9981832/ | [
"Hongtao Wu",
"Jikai Ye",
"Xin Meng",
"Chris Paxton",
"Gregory S. Chirikjian",
"Hongtao Wu",
"Jikai Ye",
"Xin Meng",
"Chris Paxton",
"Gregory S. Chirikjian"
] | Rearrangement tasks have been identified as a crucial challenge for intelligent robotic manipulation, but few methods allow for precise construction of unseen structures. We propose a visual foresight model for pick-and-place rearrangement manipulation which is able to learn efficiently. In addition, we develop a multi-modal action proposal module which builds on the Goal-Conditioned Transporter N... |
Extending extrapolation capabilities of probabilistic motion models learned from human demonstrations using shape-preserving virtual demonstrations | https://ieeexplore.ieee.org/document/9982222/ | [
"Riccardo Burlizzi",
"Maxim Vochten",
"Joris De Schutter",
"Erwin Aertbeliën",
"Riccardo Burlizzi",
"Maxim Vochten",
"Joris De Schutter",
"Erwin Aertbeliën"
] | Learning from Demonstration (LfD) requires methodologies able to generalize tasks in new situations. This paper studies the use of virtual demonstrations to extend the extrapolation capabilities of probabilistic motion models such as the traPPCA method. Similarly to other LfD methods, traPPCA is able to calculate new trajectories very fast, but does not generalize well outside the area covered by ... |
Learning High Speed Precision Table Tennis on a Physical Robot | https://ieeexplore.ieee.org/document/9982205/ | [
"Tianli Ding",
"Laura Graesser",
"Saminda Abeyruwan",
"David B. D'Ambrosio",
"Anish Shankar",
"Pierre Sermanet",
"Pannag R. Sanketi",
"Corey Lynch",
"Tianli Ding",
"Laura Graesser",
"Saminda Abeyruwan",
"David B. D'Ambrosio",
"Anish Shankar",
"Pierre Sermanet",
"Pannag R. Sanketi",
"Corey Lynch"
] | Learning goal conditioned control in the real world is a challenging open problem in robotics. Reinforcement learning systems have the potential to learn autonomously via trial-and-error, but in practice the costs of manual reward design, ensuring safe exploration, and hyperparameter tuning are often enough to preclude real world deployment. Imitation learning approaches, on the other hand, offer ... |
Behaviour Learning with Adaptive Motif Discovery and Interacting Multiple Model | https://ieeexplore.ieee.org/document/9981588/ | [
"Hanging Zhao",
"Travis Manderson",
"Hao Zhang",
"Xue Liu",
"Gregory Dudek",
"Hanging Zhao",
"Travis Manderson",
"Hao Zhang",
"Xue Liu",
"Gregory Dudek"
] | We propose an approach that enables simultaneous interpretable learning of a high-level discrete behaviour and its low-level rhythmic sub-behaviour. We do this though a unified reward function, where a reward function that only describes low-level behaviour, with less impact on learning of other behaviours is recovered from few-shot motion demonstrations. To this end, we first extract local behavi... |
Learning from Demonstration using a Curvature Regularized Variational Auto-Encoder (CurvVAE) | https://ieeexplore.ieee.org/document/9981930/ | [
"Travers Rhodes",
"Tapomayukh Bhattacharjee",
"Daniel D. Lee",
"Travers Rhodes",
"Tapomayukh Bhattacharjee",
"Daniel D. Lee"
] | Learning intricate manipulation skills from human demonstrations requires good sample efficiency. We introduce a novel learning algorithm, the Curvature-regularized Variational Auto-Encoder (CurvVAE), to achieve this goal. The CurvVAE is able to model the natural variations in human-demonstrated trajectory data without overfitting. It does so by regularizing the curvature of the learned manifold. ... |
Bayesian Active Learning for Sim-to-Real Robotic Perception | https://ieeexplore.ieee.org/document/9982175/ | [
"Jianxiang Feng",
"Jongseok Lee",
"Maximilian Durner",
"Rudolph Triebel",
"Jianxiang Feng",
"Jongseok Lee",
"Maximilian Durner",
"Rudolph Triebel"
] | While learning from synthetic training data has recently gained an increased attention, in real-world robotic applications, there are still performance deficiencies due to the so-called Sim-to-Real gap. In practice, this gap is hard to resolve with only synthetic data. Therefore, we focus on an efficient acquisition of real data within a Sim-to-Real learning pipeline. Concretely, we employ deep Ba... |
DiffCloud: Real-to-Sim from Point Clouds with Differentiable Simulation and Rendering of Deformable Objects | https://ieeexplore.ieee.org/document/9981101/ | [
"Priya Sundaresan",
"Rika Antonova",
"Jeannette Bohgl",
"Priya Sundaresan",
"Rika Antonova",
"Jeannette Bohgl"
] | Research in manipulation of deformable objects is typically conducted on a limited range of scenarios, because handling each scenario on hardware takes significant effort. Realistic simulators with support for various types of deformations and interactions have the potential to speed up experimentation with novel tasks and algorithms. However, for highly deformable objects it is challenging to ali... |
Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments | https://ieeexplore.ieee.org/document/9981323/ | [
"Maneekwan Toyungyernsub",
"Esen Yel",
"Jiachen Li",
"Mykel J. Kochenderfer",
"Maneekwan Toyungyernsub",
"Esen Yel",
"Jiachen Li",
"Mykel J. Kochenderfer"
] | Detection and segmentation of moving obstacles, along with prediction of the future occupancy states of the local environment, are essential for autonomous vehicles to proactively make safe and informed decisions. In this paper, we propose a framework that integrates the two capabilities together using deep neural network architectures. Our method first detects and segments moving objects in the s... |
Pseudo-label Guided Cross-video Pixel Contrast for Robotic Surgical Scene Segmentation with Limited Annotations | https://ieeexplore.ieee.org/document/9981798/ | [
"Yang Yu",
"Zixu Zhao",
"Yueming Jin",
"Guangyong Chen",
"Qi Dou",
"Pheng-Ann Heng",
"Yang Yu",
"Zixu Zhao",
"Yueming Jin",
"Guangyong Chen",
"Qi Dou",
"Pheng-Ann Heng"
] | Surgical scene segmentation is fundamentally crucial for prompting cognitive assistance in robotic surgery. However, pixel-wise annotating surgical video in a frame-by-frame manner is expensive and time consuming. To greatly reduce the labeling burden, in this work, we study semi-supervised scene segmentation from robotic surgical video, which is practically essential yet rarely explored before. W... |
An Unsupervised Domain Adaptive Approach for Multimodal 2D Object Detection in Adverse Weather Conditions | https://ieeexplore.ieee.org/document/9982109/ | [
"George Eskandar",
"Robert A. Marsden",
"Pavithran Pandiyan",
"Mario Döbler",
"Karim Guirguis",
"Bin Yang",
"George Eskandar",
"Robert A. Marsden",
"Pavithran Pandiyan",
"Mario Döbler",
"Karim Guirguis",
"Bin Yang"
] | Integrating different representations from complementary sensing modalities is crucial for robust scene interpretation in autonomous driving. While deep learning architectures that fuse vision and range data for 2D object detection have thrived in recent years, the corresponding modalities can degrade in adverse weather or lighting conditions, ultimately leading to a drop in performance. Although ... |
Multiscale Sensor Fusion and Continuous Control with Neural CDEs | https://ieeexplore.ieee.org/document/9982210/ | [
"Sumeet Singh",
"Francis McCann Ramirez",
"Jacob Varley",
"Andy Zeng",
"Vikas Sindhwani",
"Sumeet Singh",
"Francis McCann Ramirez",
"Jacob Varley",
"Andy Zeng",
"Vikas Sindhwani"
] | Though robot learning is often formulated in terms of discrete-time Markov decision processes (MDPs), physical robots require near-continuous multiscale feedback control. Machines operate on multiple asynchronous sensing modalities, each with different frequencies, e.g., video frames at 30Hz, proprioceptive state at 100Hz, force-torque data at 500Hz, etc. While the classic approach is to batch obs... |
SMS-MPC: Adversarial Learning-based Simultaneous Prediction Control with Single Model for Mobile Robots | https://ieeexplore.ieee.org/document/9981289/ | [
"Andong Yang",
"Wei Li",
"Yu Hu",
"Andong Yang",
"Wei Li",
"Yu Hu"
] | Model predictive control is a promising method in robot control tasks. How to design an effective model structure and efficient prediction framework for model predictive control is still an open challenge. To reduce the time consumption and avoid compounding-error of the multi-step prediction process in model predictive control, we propose a single-model simultaneous framework, which uses single d... |
Dynamic Inference on Graphs using Structured Transition Models | https://ieeexplore.ieee.org/document/9981449/ | [
"Saumya Saxena",
"Oliver Kroemer",
"Saumya Saxena",
"Oliver Kroemer"
] | Enabling robots to perform complex dynamic tasks such as picking up an object in one sweeping motion or pushing off a wall to quickly turn a corner is a challenging problem. The dynamic interactions implicit in these tasks are critical towards the successful execution of such tasks. Graph neural networks (GNNs) provide a principled way of learning the dynamics of interactive systems but can suffer... |
Grasp Planning for Occluded Objects in a Confined Space with Lateral View Using Monte Carlo Tree Search | https://ieeexplore.ieee.org/document/9981069/ | [
"Minjae Kang",
"Hogun Kee",
"Junseok Kim",
"Songhwai Oh",
"Minjae Kang",
"Hogun Kee",
"Junseok Kim",
"Songhwai Oh"
] | In the lateral access environment, the robot be-havior should be planned considering surrounding objects and obstacles because object observation directions and approach angles are limited. To safely retrieve a partially occluded target object in these environments, we have to relocate objects using prehensile actions to create a collision-free path for the target. We propose a learning-based meth... |
Non-blocking Asynchronous Training for Reinforcement Learning in Real-World Environments | https://ieeexplore.ieee.org/document/9981333/ | [
"Peter Böhm",
"Pauline Pounds",
"Archie C. Chapman",
"Peter Böhm",
"Pauline Pounds",
"Archie C. Chapman"
] | Deep Reinforcement Learning (DRL) faces challenges bridging the sim-to-real gap to enable real-world applications. In contrast to the simulated environments used in conventional DRL training, real-world systems are non-linear and evolve in an asynchronous fashion; sensors and actuators have limited precision; communication channels are noisy; and many components introduce variable delays. While th... |
Robot Skill Learning with Identification of Preconditions and Postconditions via Level Set Estimation | https://ieeexplore.ieee.org/document/9981933/ | [
"Rin Takano",
"Hiroyuki Oyama",
"Yuki Taya",
"Rin Takano",
"Hiroyuki Oyama",
"Yuki Taya"
] | Hierarchical algorithms have often been used to plan and execute complicated robotic sequential manipulation tasks, where an abstract planner searches for a skill sequence in an abstract space, and each skill generates actual motions on the basis of the planned skill sequences. To generate executable plans, the abstract planner should know the pre-/postconditions of each skill and appropriately ch... |
Sex Parity in Cognitive Fatigue Model Development for Effective Human-Robot Collaboration | https://ieeexplore.ieee.org/document/9981097/ | [
"Apostolos Kalatzis",
"Sarah Hopko",
"Ranjana K. Mehta",
"Laura Stanley",
"Mike P. Wittie",
"Apostolos Kalatzis",
"Sarah Hopko",
"Ranjana K. Mehta",
"Laura Stanley",
"Mike P. Wittie"
] | In recent years, robots have become vital to achieving manufacturing competitiveness. Especially in industrial environments, a strong level of interaction is reached when humans and robots form a dynamic system that works together towards achieving a common goal or accomplishing a task. However, the human-robot collaboration can be cognitively demanding, potentially contributing to cognitive fatig... |
Online Adaptive Compensation for Model Uncertainty Using Extreme Learning Machine-based Control Barrier Functions | https://ieeexplore.ieee.org/document/9981680/ | [
"Emanuel Munoz",
"Dvij Kalaria",
"Qin Lin",
"John M. Dolan",
"Emanuel Munoz",
"Dvij Kalaria",
"Qin Lin",
"John M. Dolan"
] | A control barrier functions-based quadratic programming (CBF-QP) method has emerged as a controller synthesis tool to assure safety of autonomous systems owing to the appealing safe forward invariant set. However, the provable safety relies on a precisely described dynamic model, which is not always available in practice. Recent works leverage learning to compensate model uncertainty for a CBF con... |
Task-Space Control of Continuum Robots using Underactuated Discrete Rod Models | https://ieeexplore.ieee.org/document/9982271/ | [
"Caleb Rucker",
"Eric J. Barth",
"Joshua Gaston",
"James C. Gallentine",
"Caleb Rucker",
"Eric J. Barth",
"Joshua Gaston",
"James C. Gallentine"
] | Underactuation is a core challenge associated with controlling soft and continuum robots, which possess theoreti-cally infinite degrees of freedom, but few actuators. However, $m$ actuators may still be used to control a dynamic soft robot in an m-dimensional output task space. In this paper we develop a task-space control approach for planar continuum robots that is robust to modeling error and r... |
Omnidirectional walking of a quadruped robot enabled by compressible tendon-driven soft actuators | https://ieeexplore.ieee.org/document/9981314/ | [
"Qinglei Ji",
"Shuo Fu",
"Lei Feng",
"George Andrikopoulos",
"Xi Vincent Wang",
"Lihui Wang",
"Qinglei Ji",
"Shuo Fu",
"Lei Feng",
"George Andrikopoulos",
"Xi Vincent Wang",
"Lihui Wang"
] | Using soft actuators as legs, soft quadruped robots have shown great potential in traversing unstructured and complex terrains and environments. However, unlike rigid robots whose gaits can be generated using foot pattern design and kinematic model of the rigid legs, the gait generation of soft quadruped robots remains challenging due to the high DoFs of the soft actuators and the uncertain deform... |
Learning physics-informed simulation models for soft robotic manipulation: A case study with dielectric elastomer actuators | https://ieeexplore.ieee.org/document/9981373/ | [
"Manu Lahariya",
"Craig Innes",
"Chris Develder",
"Subramanian Ramamoorthy",
"Manu Lahariya",
"Craig Innes",
"Chris Develder",
"Subramanian Ramamoorthy"
] | Soft actuators offer a safe, adaptable approach to tasks like gentle grasping and dexterous manipulation. Creating accurate models to control such systems however is challenging due to the complex physics of deformable materials. Accurate Finite Element Method (FEM) models incur prohibitive computational complexity for closed-loop use. Using a differentiable simulator is an attractive alternative,... |
Detecting Invalid Map Merges in Lifelong SLAM | https://ieeexplore.ieee.org/document/9981564/ | [
"Matthias Holoch",
"Gerhard Kurz",
"Peter Biber",
"Matthias Holoch",
"Gerhard Kurz",
"Peter Biber"
] | For Lifelong SLAM, one has to deal with temporary localization failures, e.g., induced by kidnapping. We achieve this by starting a new map and merging it with the previous map as soon as relocalization succeeds. Since relocalization methods are fallible, it can happen that such a merge is invalid, e.g., due to perceptual aliasing. To address this issue, we propose methods to detect and undo inval... |
MD-SLAM: Multi-cue Direct SLAM | https://ieeexplore.ieee.org/document/9981147/ | [
"Luca Di Giammarino",
"Leonardo Brizi",
"Tiziano Guadagnino",
"Cyrill Stachniss",
"Giorgio Grisetti",
"Luca Di Giammarino",
"Leonardo Brizi",
"Tiziano Guadagnino",
"Cyrill Stachniss",
"Giorgio Grisetti"
] | Simultaneous Localization and Mapping (SLAM) systems are fundamental building blocks for any autonomous robot navigating in unknown environments. The SLAM implementation heavily depends on the sensor modality employed on the mobile platform. For this reason, assumptions on the scene's structure are often made to maximize estimation accuracy. This paper presents a novel direct 3D SLAM pipeline that... |
Visual-Inertial Multi-Instance Dynamic SLAM with Object-level Relocalisation | https://ieeexplore.ieee.org/document/9981795/ | [
"Yifei Ren",
"Binbin Xu",
"Christopher L. Choi",
"Stefan Leutenegger",
"Yifei Ren",
"Binbin Xu",
"Christopher L. Choi",
"Stefan Leutenegger"
] | In this paper, we present a tightly-coupled visual-inertial object-level multi-instance dynamic SLAM system. Even in extremely dynamic scenes, it can robustly optimise for the camera pose, velocity, IMU biases and build a dense 3D reconstruction object-level map of the environment. Our system can robustly track and reconstruct the geometries of arbitrary objects, their semantics and motion by incr... |
ACEFusion - Accelerated and Energy-Efficient Semantic 3D Reconstruction of Dynamic Scenes | https://ieeexplore.ieee.org/document/9981591/ | [
"Mihai Bujanca",
"Barry Lennox",
"Mikel Luján",
"Mihai Bujanca",
"Barry Lennox",
"Mikel Luján"
] | ACEFusion is the first 3D reconstruction system able to capture the geometry and semantics of dynamic scenes using an RGB-D camera in real-time on a robotic computing platform. Harnessing the hardware accelerators of an Nvidia Jetson AGX Xavier, the system uses heterogeneous computing to achieve 30 FPS under a 30W power budget. Using a data-parallel design, we perform most image computation on the... |
PFilter: Building Persistent Maps through Feature Filtering for Fast and Accurate LiDAR-based SLAM | https://ieeexplore.ieee.org/document/9981566/ | [
"Yifan Duan",
"Jie Peng",
"Yu Zhang",
"Jianmin Ji",
"Yanyong Zhang",
"Yifan Duan",
"Jie Peng",
"Yu Zhang",
"Jianmin Ji",
"Yanyong Zhang"
] | Simultaneous localization and mapping (SLAM) based on laser sensors has been widely adopted by mobile robots and autonomous vehicles. These SLAM systems are required to support accurate localization with limited computational resources. In particular, point cloud registration, i.e., the process of matching and aligning multiple LiDAR scans collected at multiple locations in a global coordinate fra... |
City-wide Street-to-Satellite Image Geolocalization of a Mobile Ground Agent | https://ieeexplore.ieee.org/document/9981996/ | [
"Lena M. Downes",
"Dong-Ki Kim",
"Ted J. Steiner",
"Jonathan P. How",
"Lena M. Downes",
"Dong-Ki Kim",
"Ted J. Steiner",
"Jonathan P. How"
] | Cross-view image geolocalization provides an estimate of an agent's global position by matching a local ground image to an overhead satellite image without the need for GPS. It is challenging to reliably match a ground image to the correct satellite image since the images have significant viewpoint differences. Existing works have demonstrated localization in constrained scenarios over small areas... |
Soft Actuators for Facial Reanimation | https://ieeexplore.ieee.org/document/9982089/ | [
"Stefania Konstantinidi",
"Thomas Martinez",
"Amine Benouhiba",
"Yoan Civet",
"Yves Perriard",
"Stefania Konstantinidi",
"Thomas Martinez",
"Amine Benouhiba",
"Yoan Civet",
"Yves Perriard"
] | Facial paralysis is a challenging condition that alters a patient's ability to express emotion and communicate. Restoring facial movements thus has crucial implications for the patients' quality of life. This publication introduces an approach for artificial muscles implementation targeting facial reanimation, as well as the challenges and limitations of the proposed strategy. The aim is to develo... |
Development and Experimental Evaluation of a Novel Portable Haptic Robotic Exoskeleton Glove System for Patients with Brachial Plexus Injuries | https://ieeexplore.ieee.org/document/9981468/ | [
"Wenda Xu",
"Yunfei Guo",
"Cesar Bravo",
"Pinhas Ben-Tzvi",
"Wenda Xu",
"Yunfei Guo",
"Cesar Bravo",
"Pinhas Ben-Tzvi"
] | This paper presents the development and experimental evaluation of a portable haptic exoskeleton glove system designed for people who suffer from brachial plexus injuries to restore their lost grasping functionality. The proposed glove system involves force perception, linkage-driven finger mechanism, and personalized voice control to achieve various grasping functionality requirements. The fully ... |
Development of a Novel Low-profile Robotic Exoskeleton Glove for Patients with Brachial Plexus Injuries | https://ieeexplore.ieee.org/document/9981124/ | [
"Wenda Xu",
"Yujiong Liu",
"Pinhas Ben-Tzvi",
"Wenda Xu",
"Yujiong Liu",
"Pinhas Ben-Tzvi"
] | This paper presents the design and development of a novel, low-profile, exoskeleton robotic glove aimed for people who suffer from brachial plexus injuries to restore their lost grasping functionality. The key idea of this new glove lies in its new finger mechanism that takes advantage of the rigid coupling hybrid mechanism (RCHM) concept. This mechanism concept couples the motions of the adjacent... |
A Novel Wheelchair-Exoskeleton Hybrid Robot to Assist Movement and Aid Rehabilitation | https://ieeexplore.ieee.org/document/9981240/ | [
"Zhibin Song",
"Wenjie Ju",
"Dechao Chen",
"Hexi Gong",
"Rongjie Kang",
"Paolo Dario",
"Zhibin Song",
"Wenjie Ju",
"Dechao Chen",
"Hexi Gong",
"Rongjie Kang",
"Paolo Dario"
] | As a traditional movement assist equipment for people with lower-limb dysfunction, the wheelchair can support and carry users to perform a long-distance movement indoor and outdoor, however, prolonged inactivity can lead to muscle atrophy and deteriorate motion functions. As a promising solution, the lower limb exoskeleton provides people the ability of standing and walking to avoid these problems... |
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