Search-based techniques have shown great success in motion planning problems such as robotic navigation by discretizing the state space and precomputing motion primitives. However in domains with complex dynamic constraints, constructing motion primitives in a discretized state space is non-trivial. This requires operating in continuous space which can be challenging for search-based planners as they can get stuck in local minima regions. Previous work on planning in continuous spaces introduced soft duplicate detection which requires search to compute the duplicity of a state with respect to previously seen states to avoid exploring states that are likely to be duplicates, especially in local minima regions. They propose a simple metric utilizing the euclidean distance between states, and proximity to obstacles to compute the duplicity. In this paper, we improve upon this metric by introducing a kinodynamically informed metric, subtree overlap, between two states as the similarity between their successors that can be reached within a fixed time horizon using kinodynamic motion primitives. This captures the intuition that, due to robot dynamics, duplicate states can be far in euclidean distance and result in very similar successor states, while non-duplicate states can be close and result in widely different successors.
Shape-Space Graphs: Fast and Collision-Free Path Planning for Soft Robots
Department of Mechanical Engineering, Stanford University（机械工程系，斯坦福大学）；Institute of Applied Mechanics, Friedrich-Alexander-Universität Erlangen–Nürnberg（应用力学研究所，弗赖堡-埃尔兰根-纽伦堡大学）
Underwater Multi-Robot Simulation and Motion Planning in Angler
Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University（协作机器人与智能系统研究所，俄勒冈州立大学）；Department of Computer Science, Purdue University（计算机科学系，普渡大学）
Shell-Type Soft Jig for Holding Objects during Disassembly
Department of Systems Innovation, Graduate School of Engineering Science, The University of Osaka（大阪大学工学系研究生院系统创新部门）；Industrial Cyber-physical Systems Research Center, The National Institute of Advanced Industrial Science and Technology (AIST)（国家先进工业科学与技术研究院工业闭环系统研究中心）
Unified Complementarity-Based Contact Modeling and Planning for Soft Robots
Woodruff School of Mechanical Engineering and the Institute for Robotics and Intelligent Machines (IRIM), Georgia Institute of Technology（伍德鲁夫机械工程学院和机器人与智能机器研究所（IRIM）、佐治亚理工学院）；Coulter Department of Biomedical Engineering (Georgia Tech and Emory University) and the Institute for Robotics and Intelligent Machines (IRIM), Georgia Institute of Technology（库勒生物医学工程系（佐治亚理工学院和埃默里大学）和机器人与智能机器研究所（IRIM）、佐治亚理工学院）
A Versatile Neural Network Configuration Space Planning and Control Strategy for Modular Soft Robot Arms
Biorobotics Institute and the Department of Excellence in Robotics and AI（生物机器人研究所和机器人与人工智能卓越部门）；Scuola Superiore Sant’Anna（圣安娜高等学院）；CREATE Lab（CREATE实验室）；EPFL（瑞士联邦理工学院）
