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A Cartesian-Based Trajectory Optimization with Jerk Constraints for a Robot.

Authors :
Fan, Zhiwei
Jia, Kai
Zhang, Lei
Zou, Fengshan
Du, Zhenjun
Liu, Mingmin
Cao, Yuting
Zhang, Qiang
Source :
Entropy. Apr2023, Vol. 25 Issue 4, p610. 21p.
Publication Year :
2023

Abstract

To address the time-optimal trajectory planning (TOTP) problem with joint jerk constraints in a Cartesian coordinate system, we propose a time-optimal path-parameterization (TOPP) algorithm based on nonlinear optimization. The key insight of our approach is the presentation of a comprehensive and effective iterative optimization framework for solving the optimal control problem (OCP) formulation of the TOTP problem in the (s , s ˙) -phase plane. In particular, we identify two major difficulties: establishing TOPP in Cartesian space satisfying third-order constraints in joint space, and finding an efficient computational solution to TOPP, which includes nonlinear constraints. Experimental results demonstrate that the proposed method is an effective solution for time-optimal trajectory planning with joint jerk limits, and can be applied to a wide range of robotic systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10994300
Volume :
25
Issue :
4
Database :
Academic Search Index
Journal :
Entropy
Publication Type :
Academic Journal
Accession number :
163384862
Full Text :
https://doi.org/10.3390/e25040610