中文版 | English
Title

Motion Planning for Nonlinear Robotic System based on ADMM and Convex Feasible Set Algorithm

Author
DOI
Publication Years
2022
Conference Name
IEEE 61st Conference on Decision and Control (CDC)
ISSN
0743-1546
EISSN
2576-2370
ISBN
978-1-6654-6762-9
Source Title
Pages
7461-7466
Conference Date
6-9 Dec. 2022
Conference Place
Cancun, Mexico
Publication Place
345 E 47TH ST, NEW YORK, NY 10017 USA
Publisher
Abstract
In the motion planning of robot, nonlinear dynamic constraints and obstacle avoidance constraints make the problem highly non-convex and difficult to solve. In this paper, a general algorithmic framework for trajectory optimization is proposed based on alternating direction method of multipliers (ADMM) and convex feasible set algorithm (CFS). The ADMM framework decomposes the original problem into an optimal control sub-problem with only dynamic constraints and a sub-problem with only obstacle avoidance constraints, while the sub-problem with obstacle avoidance constraints is solved via CFS based on the geometric properties of the feasible region. The convergence of proposed algorithm is proven, and the simulation results in different cases verify the feasibility and effectiveness of proposed algorithm.
Keywords
SUSTech Authorship
First
Language
English
URL[Source Record]
Indexed By
Funding Project
National Key Research and Development Program of China[2019YFB1705401] ; Natural Science Foundation of China[61873118] ; Science, Technology and Innovation Commission of Shenzhen Municipality["20200925174707002","ZDSYS20200811143601004"]
WOS Research Area
Automation & Control Systems ; Engineering
WOS Subject
Automation & Control Systems ; Engineering, Electrical & Electronic
WOS Accession No
WOS:000948128106037
Data Source
IEEE
PDF urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9992594
Citation statistics
Cited Times [WOS]:0
Document TypeConference paper
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/424409
DepartmentDepartment of Mechanical and Energy Engineering
Affiliation
Department of Mechanical and Energy Engineering, and the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Southern University of Science and Technology, Shenzhen, China
First Author AffilicationDepartment of Mechanical and Energy Engineering
First Author's First AffilicationDepartment of Mechanical and Energy Engineering
Recommended Citation
GB/T 7714
Ruishuang Chen,Zaiyue Yang,Jie Cheng,et al. Motion Planning for Nonlinear Robotic System based on ADMM and Convex Feasible Set Algorithm[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2022:7461-7466.
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