Time-Optimal Exponential Trajectory Planning of Robotic Systems under Kinematic Constraints
Pages 1766 - 1772
Abstract
This paper presents a novel time-optimal trajectory planning method designed for robotic systems with multi-degree-of-freedom (DOF). The proposed approach utilizes an exponential function as the basis for the velocity profile, enabling point-to-point trajectory generation with significant advantages in terms of smooth motion and ease of planning. The previous exponential trajectory planning approach appears to be slightly less efficient than traditional methods and could potentially compromise accuracy at waypoints, as it relies on constant parameters without considering time optimization. To improve motion accuracy and efficiency in the operation of multi-DOF robotic systems, the proposed method optimizes trajectories to minimize execution time while ensuring motion smoothness under the constraints imposed by the robot's kinematics. Numerical examples on a 3-DOF robotic arm demonstrate the superiority of the proposed method, showcasing improved position accuracy and motion quality. The presented time-optimal exponential trajectory planning method may offer a valuable tool for optimizing robotic performance, enhancing productivity, and enabling precise motion control in various robotic applications.
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Index Terms
- Time-Optimal Exponential Trajectory Planning of Robotic Systems under Kinematic Constraints
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Published In
October 2023
1809 pages
ISBN:9798400708305
DOI:10.1145/3650400
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 17 April 2024
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- Research-article
- Research
- Refereed limited
Funding Sources
- Research Start-up Fund Project of Hainan University
- Natural Science Foundation of Hainan Province
- Scientific research project of Institutions of Higher Education in Hainan Province
- Natural Science Foundation of Hainan Province
Conference
EITCE 2023
EITCE 2023: 2023 7th International Conference on Electronic Information Technology and Computer Engineering
October 20 - 22, 2023
Xiamen, China
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Overall Acceptance Rate 508 of 972 submissions, 52%
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