@inproceedings{d7eb1afb670b48b9b70c75b5de2ccc36,
title = "A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence",
abstract = "This paper presents, Anytime Fast-BIT∗ (AFBIT∗), a sampling based, asymptotically optimal manipulation motion planner which quickly finds an initial feasible path and rapidly improves the path quality toward optimality. AFBIT∗ is guided by modified heuristics in task space for faster first solution. A local optimization method is adopted at the end of every round to optimize the current best path and generate the next vertex and edge for the global path while a new round begins to improve the quality of the remaining path. Simulation results suggest AFBIT∗ is more efficient and effective on manipulation problems than BIT∗ and Fast-BIT∗.",
keywords = "Industrial robots, Manipulation motion planning, Sampling-Based Algorithm",
author = "Guoqiang Zhao and Xiangzhou Wang and Shuhua Zheng and Qian Han",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 34th Chinese Control and Decision Conference, CCDC 2022 ; Conference date: 15-08-2022 Through 17-08-2022",
year = "2022",
doi = "10.1109/CCDC55256.2022.10033427",
language = "English",
series = "Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "357--363",
booktitle = "Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022",
address = "United States",
}