Provably Safe Trajectory Generation for Manipulators Under Motion and Environmental Uncertainties
Hong Kong Center for Construction Robotics, The Hong Kong University of Science and Technology（香港建设机器人中心，香港理工大学）；Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong（机械与自动化工程系，中国香港大学）；Department of Electronic Engineering, The Chinese University of Hong Kong（电子工程系，中国香港大学）；Shenzhen Key Laboratory of Robotics Perception and Intelligence and the Department of Electronic and Electrical Engineering at Southern University of Science and Technology（深圳机器人感知与智能重点实验室和南方科技大学电子与电气工程系）；Department of Electronic Engineering at The Chinese University of Hong Kong（电子工程系，中国香港大学）
Robot manipulators operating in uncertain and non-convex environments present significant challenges for safe and optimal motion planning. Existing methods often struggle to provide efficient and formally certified collision risk guarantees, particularly when dealing with complex geometries and non-Gaussian uncertainties. This article proposes a novel risk-bounded motion planning framework to address this unmet need. Our approach integrates a rigid manipulator deep stochastic Koopman operator (RM-DeSKO) model to robustly predict the robot's state distribution under motion uncertainty. We then introduce an efficient, hierarchical verification method that combines parallelizable physics simulations with sum-of-squares (SOS) programming as a filter for fine-grained, formal certification of collision risk. This method is embedded within a Model Predictive Path Integral (MPPI) controller that uniquely utilizes binary collision information from SOS decomposition to improve its policy. The effectiveness of the proposed framework is validated on two typical robot manipulators through extensive simulations and real-world experiments, including a challenging human-robot collaboration scenario, demonstrating sim-to-real transfer of the learned model and its ability to generate safe and efficient trajectories in complex, uncertain settings.
Full-Body Dynamic Safety for Robot Manipulators: 3D Poisson Safety Functions for CBF-Based Safety Filters
Computing and Mathematical Sciences, California Institute of Technology（加州理工学院计算与数学科学系）；Mechanical and Civil Engineering, California Institute of Technology（加州理工学院机械与土木工程系）
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）
Reachable Sets for Safe, Real-Time Manipulator Trajectory Design
Mechanical Engineering, University of Michigan（密歇根大学机械工程学院）；Robotics Institute, University of Michigan（密歇根大学机器人研究所）；Mechanical and Industrial Engineering, Louisiana State University（路易斯安那州立大学机械与工业工程学院）；Naval Architecture and Marine Engineering, University of Michigan（密歇根大学船舶与海洋工程学院）；Ford Motor Company（福特汽车公司）；Office of Naval Research（美国海军研究办公室）
Safe Expeditious Whole-Body Control of Mobile Manipulators for Collision Avoidance
Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；School of Advanced Manufacturing, Sun Yat-Sen University, Sun Yat-Sen University（中山大学先进制造学院）；School of Electrical and Automation Engineering, Hefei University of Technology（合肥工业大学电气与自动化工程学院）
QuadHand: A Compact Quadrotor Aerial Manipulator with MRC-SDF-Based Whole-Body Motion Planning
Nanyang Technological University（南洋理工大学）；NTU–VinUni Joint Research Laboratory for Embodied AI and Robotics（南洋理工大学-维纳大学具身智能与机器人联合研究实验室）；VinUniversity（维纳大学）
Predictive Relative-Velocity Steering for Safe Robotic Manipulator Teleoperation in Dynamic Environments
Zhejiang University（浙江大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Tsinghua University（清华大学）；Institute for Embodied Intelligence and Robotics, Tsinghua University（清华大学具身智能与机器人研究所）；TetraBOT
Robust Convex Model Predictive Control with collision avoidance guarantees for robot manipulators
ABB robotics（ABB机器人公司）；Department of Mechanical Engineering, Imperial College London（帝国理工学院机械工程系）；Department of Information Technology, Uppsala University（乌普萨拉大学信息科技系）
Fast and Safe Trajectory Optimization for Mobile Manipulators With Neural Configuration Space Distance Field
Robotics and Autonomous Systems Thrust, The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学机器人与自主系统研究组）；Department of Electrical and Computer Engineering, National University of Singapore（新加坡国立大学电子与计算机工程系）；Idiap Research Institute（Idiap研究所）；Institute of Data Science, The University of Hong Kong（香港大学数据科学研究所）
A Closed-Form CLF-CBF Controller for Whole-Body Continuum Soft Robot Collision Avoidance
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology（计算机科学与人工智能实验室，麻省理工学院）；Robotics Engineering Department, Worcester Polytechnic Institute（机器人工程系，沃斯堡理工学院）
A Switching Nonlinear Model Predictive Control Strategy for Safe Collision Handling by an Underwater Vehicle-Manipulator System
D. Guggenheim School of Aerospace Engineering, Georgia Institute of Technology（德·古根海姆航空航天工程学院，佐治亚理工学院）；faculty of Electrical Engineering, Engineering Division, New York University Abu Dhabi（电气工程系，工程分校，纽约大学阿布扎克分校）
A study on a Real-Time VR-Based Teleoperation Framework for Manipulator in Dynamic Environment
Department of Robotics, Hanyang University（韩世大学机器人系）；Department of Smart Construction Engineering, Hanyang University（韩世大学智能建造工程系）；Department of Interdisciplinary Robot Engineering Systems, Hanyang University（韩世大学跨学科机器人工程系统系）；School of Smart Convergence Engineering, Hanyang University, Ansan（韩世大学智能融合工程学院，安山）
Admittance-Based Motion Planning with Vision-Guided Initialization for Robotic Manipulators in Self-Driving Laboratories
Department of Electronics Systems, Aalborg University（电子系统系，奥尔堡大学）；Department of Information Technology and Electrical Engineering, Università degli Studi di Napoli Federico II（信息科技与电气工程系，那不勒斯费迪里奇二世大学）
Design and Control of Modular Soft-Rigid Hybrid Manipulators with Self-Contact
Computer Science and Artificial Intelligence Laboratory, MIT（麻省理工学院计算机科学与人工智能实验室）；Delft University of Technology（代尔夫特理工大学）；German Aerospace Center (DLR)（德国航空航天中心）
