With the development of human space exploration, the space environment is gradually filled with abandoned satellite debris and unknown micrometeorites, which will seriously affect capture motion of space robot. Hence, a novel fast collision-avoidance trajectory planning strategy for a dual-arm free-floating space robot (FFSR) with predefined-time pose feedback will be mainly studied to achieve micron-level tracking accuracy of end-effector in this paper. However, similar to control, the exponential feedback results in larger initial joint angular velocity relative to proportional feedback. Firstly, a pose-error-based kinematic model of the FFSR will be derived from a control perspective. Then, a cumulative dangerous field (CDF) collision-avoidance algorithm is applied in predefined-time trajectory planning to achieve micron-level collision-avoidance trajectory tracking precision. In the end, a GA-based optimization algorithm is used to optimize the predefined-time parameter to obtain a motion trajectory of low joint angular velocity of robotic arms. The simulation results verify our conjecture and conclusion.
University of Würzburg（维尔茨堡大学）；University of Luxembourg（卢森堡大学）
Space robotics applications, such as Active Space Debris Removal (ASDR), require representative testing before launch. A commonly used approach to emulate the microgravity environment in space is air-bearing based platforms on flat-floors, such as the European Space Agency's Orbital Robotics and GNC Lab (ORGL). This work proposes a control architecture for a floating platform at the ORGL, equipped with eight solenoid-valve-based thrusters and one reaction wheel. The control architecture consists of two main components: a trajectory planner that finds optimal trajectories connecting two states …
A Comparative Study of Floating-Base Space Parameterizations for Agile Whole-Body Motion Planning
Laboratory of Automation and Robotics (LAR) in the Department of Electrical & Computer Engineering, University of Patras（帕尔蒂亚大学电气与计算机工程系自动化与机器人实验室）；Archimedes/Athena RC（阿基米德/雅典娜研究中心）；Athena - Research and Innovation Center in Information, Communication and Knowledge Technologies（雅典娜信息、通信和知识技术研究与创新中心）
Trajectory Planning for Teleoperated Space Manipulators Using Deep Reinforcement Learning
Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Research Institute of Tsinghua University in Shenzhen（清华大学深圳研究院）；Department of Automation, Tsinghua University（清华大学自动化系）
Italian Institute of Technology（意大利理工学院）；University of Genoa（热那亚大学）
Extended Kalman filtering is a common approach to achieve floating base estimation of a humanoid robot. These filters rely on measurements from an Inertial Measurement Unit (IMU) and relative forward kinematics for estimating the base position-and-orientation and its linear velocity along with the augmented states of feet position-and-orientation, thus giving them their name, flat-foot filters. However, the availability of only partial measurements often poses the question of consistency in the filter design. In this paper, we perform an experimental comparison of state-of-the-art flat-foot fi…
Optimal Trajectory Planning for Orbital Robot Rendezvous and Docking
Space Robotics Lab. (SRL) in the Department of Aerospace Engineering, Graduate School of Engineering, Tohoku University（空间机器人实验室（SRL）位于工程研究生院航空航天工程系，东北大学）
We present a trajectory planning and control architecture for bipedal locomotion at a variety of speeds on a highly underactuated and compliant bipedal robot. A library of compliant walking trajectories are planned offline, and stored as compact arrays of polynomial coefficients for tracking online. The control implementation uses a floating-base inverse dynamics controller which generates dynamically consistent feedforward torques to realize walking using information obtained from the trajectory optimization. The effectiveness of the controller is demonstrated in simulation and on hardware fo…
Istituto Italiano di Tecnologia（意大利理工学院）；Università degli Studi di Genova（热那亚大学）
In this paper, we describe a planner capable of generating walking trajectories by using the centroidal dynamics and the full kinematics of a humanoid robot model. The interaction between the robot and the walking surface is modeled explicitly through a novel contact parametrization. The approach is complementarity-free and does not need a predefined contact sequence. By solving an optimal control problem we obtain walking trajectories. In particular, through a set of constraints and dynamic equations, we model the robot in contact with the ground. We describe the objective the robot needs to …
Italian Institute of Technology（意大利技术研究院）；University of Manchester（曼彻斯特大学）；University of Genoa（热那亚大学）
The paper presents a planner to generate walking trajectories by using the centroidal dynamics and the full kinematics of a humanoid robot. The interaction between the robot and the walking surface is modeled explicitly via new conditions, the \emph{Dynamical Complementarity Constraints}. The approach does not require a predefined contact sequence and generates the footsteps automatically. We characterize the robot control objective via a set of tasks, and we address it by solving an optimal control problem. We show that it is possible to achieve walking motions automatically by specifying a m…
University of Nevada, Reno（内华达大学里诺分校）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）
The use of random sampling in decision-making and control has become popular with the ease of access to graphic processing units that can generate and calculate multiple random trajectories for real-time robotic applications. In contrast to sequential optimization, the sampling-based method can take advantage of parallel computing to maintain constant control loop frequencies. Inspired by its wide applicability in robotic applications, we calculate a sampling complexity result applicable to general nonlinear systems considered in the path integral method, which is a sampling-based method. The …
Trajectory Optimization for UAV-Based Medical Delivery with Temporal Logic Constraints and Convex Feasible Set Collision Avoidance
State Key Laboratory of Multimodal Artificial Intelligence Systems（多模态人工智能系统国家重点实验室）；Vanke School of Public Health（万科公共卫生学院）；School of Automation（自动化学院）
Physics-Driven Data Generation for Contact-Rich Manipulation via Trajectory Optimization
Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology（计算机科学与人工智能实验室（CSAIL），麻省理工学院）；Robotics and AI Institute（机器人与人工智能研究院）
Enhancing Model-Based Step Adaptation for Push Recovery through Reinforcement Learning of Step Timing and Region
Automation and Control Institute, TU Wien（维也纳工业大学自动化与控制研究所）；Autonomous Systems Lab, TU Wien（维也纳工业大学自主系统实验室）；Institute of Robotics and Mechatronics (DLR), German Aerospace Center（德国航空航天中心机器人与机电一体化研究所（DLR））
Real-Time Communication-Aware Ride-Sharing Route Planning for Urban Air Mobility: A Multi-Source Hybrid Attention Reinforcement Learning Approach
School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen（科学与工程学院，香港中文大学（深圳））；Xidian University State Key Laboratory of Integrated Services Network（西安电子科技大学集成服务网络国家重点实验室）；Department of Computer Science and Engineering, Kyung Hee University（庆北大学计算机科学与工程系）
Multi-robot Aerial Soft Manipulator For Floating Litter Collection
GRVC Robotics Lab, Escuela Tecnica Superior de Ingenieria, Universidad de Sevilla（塞维利亚大学技术与工程学院机器人实验室）；Robotics and Mechatronics Department, Electrical Engineering, Mathematics, and Computer Science (EEMCS) Faculty, University of Twente（特文特大学机器人与机电部门）；Inria, Univ. Rennes, CNRS, IRISA（法国国家信息与自动化技术研究院（Inria））；Department of Computer, Control and Management Engineering, Sapienza University of Rome（罗马大学计算机、控制与管理工程系）
In this work we present a constructive method to design a family of virtual contraction based controllers that solve the standard trajectory tracking problem of flexible-joint robots (FJRs) in the port-Hamiltonian (pH) framework. The proposed design method, called virtual contraction based control (v-CBC), combines the concepts of virtual control systems and contraction analysis. It is shown that under potential energy matching conditions, the closed-loop virtual system is contractive and exponential convergence to a predefined trajectory is guaranteed. Moreover, the closed-loop virtual system…
MetaFold: Language-Guided Multi-Category Garment Folding Framework via Trajectory Generation and Foundation Model
School of Computing, National University of Singapore（新加坡国立大学计算机学院）；NUS Guangzhou Research Translation and Innovation Institute（新加坡国立大学广州翻译与创新研究院）；School of Computer Science, Nanjing University（南京大学计算机学院）；School of Computer Science, Peking University（北京大学计算机学院）；School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University（上海交通大学电子信息与电气工程学院）
Accuracy and repeatability of a parallel robot for personalised minimally invasive surgery
CESTER, Technical University of Cluj-Napoca（克卢日-纳波卡技术大学 CESTER）；École Centrale Nantes, Nantes Université, CNRS, LS2N（南特中央理工大学、南特大学、法国国家科学研究中心、LS2N）；Technical Sciences Academy of Romania（罗马尼亚技术科学院）
Well-established optimization-based methods can guarantee an optimal trajectory for a short optimization horizon, typically no longer than a few seconds. As a result, choosing the optimal trajectory for this short horizon may still result in a sub-optimal long-term solution. At the same time, the resulting short-term trajectories allow for effective, comfortable and provable safe maneuvers in a dynamic traffic environment. In this work, we address the question of how to ensure an optimal long-term driving strategy, while keeping the benefits of classical trajectory planning. We introduce a Rei…
Safe Obstacle-Free Guidance of Space Manipulators in Debris Removal Missions via Deep Reinforcement Learning
Embodied Learning and Intelligence for eXploration and Innovative soft Robotics (ELIXIR) Lab, Toronto Metropolitan University, Toronto, ON, Canada（体现学习与智能探索与创新软机器人（ELIXIR）实验室，多伦多 Metropolitan 大学，多伦多，ON，加拿大）
DPNet: Efficient Dead-End Prediction and Avoidance for Vision-Based UAV Navigation
Huzhou Institute of Zhejiang University（浙江大学湖州研究院）；University of Electronic Science and Technology of China（电子科技大学）；Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University（浙江大学控制科学与工程学院 cyber系统与控制研究所）；Differential Robotics Technology Company（差分机器人技术公司）
Interaction-Stiffness-Guided Basis Allocation in Dynamic Movement Primitives for Efficient Skill Transfer
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences（中国科学院宁波材料技术与工程研究所）；University of Chinese Academy of Sciences（中国科学院大学）；The Hong Kong Polytechnic University（香港理工大学）
Istituto Italiano di Tecnologia（意大利理工学院）；ETH Zurich（苏黎世联邦理工学院）
We present a framework for dynamic quadrupedal locomotion over challenging terrain, where the choice of appropriate footholds is crucial for the success of the behaviour. We build a model of the environment on-line and on-board using an efficient occupancy grid representation. We use Any-time-Repairing A* (ARA*) to search over a tree of possible actions, choose a rough body path and select the locally-best footholds accordingly. We run a n-step lookahead optimization of the body trajectory using a dynamic stability metric, the Zero Moment Point (ZMP), that generates natural dynamic whole-body …
