TY - GEN
T1 - Adaptive Planning of Optimal Grinding Path based on Improved MAX-MIN Ant System
AU - Wang, Ningyuan
AU - Wang, Qiang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In grinding tasks of robotic arms, grinding efficiency is a very important factor. In this paper, an efficient grinding path planning is proposed to improve grinding efficiency by adaptively shortening grinding path as much as possible for workpieces with unknown sizes and arbitrary surface characteristics. First, the size of workpiece is calculated based on information of all points to be ground, and the length of the shortest path along the surface of workpiece between arbitrary two points is obtained based on workpiece size. Second, MAX-MIN Ant System (MMAS) is improved through modifications of pheromone concentration update mechanism as well as the adding of pheromone concentration disturbance to enhance its efficiency and optimization capability, and improved-MMAS is applied in optimal sorting algorithm to adaptively generate the shortest grinding path on the workpiece with arbitrary surface characteristics. Experiment results validate that the proposed grinding path planning can adaptively generate the shortest grinding path on workpieces with unknown sizes and arbitrary surface characteristics.
AB - In grinding tasks of robotic arms, grinding efficiency is a very important factor. In this paper, an efficient grinding path planning is proposed to improve grinding efficiency by adaptively shortening grinding path as much as possible for workpieces with unknown sizes and arbitrary surface characteristics. First, the size of workpiece is calculated based on information of all points to be ground, and the length of the shortest path along the surface of workpiece between arbitrary two points is obtained based on workpiece size. Second, MAX-MIN Ant System (MMAS) is improved through modifications of pheromone concentration update mechanism as well as the adding of pheromone concentration disturbance to enhance its efficiency and optimization capability, and improved-MMAS is applied in optimal sorting algorithm to adaptively generate the shortest grinding path on the workpiece with arbitrary surface characteristics. Experiment results validate that the proposed grinding path planning can adaptively generate the shortest grinding path on workpieces with unknown sizes and arbitrary surface characteristics.
KW - MMAS
KW - adaptive grinding planning
KW - optimal grinding path
KW - optimal sorting
UR - https://www.scopus.com/pages/publications/85181834177
U2 - 10.1109/CCDC58219.2023.10327015
DO - 10.1109/CCDC58219.2023.10327015
M3 - 会议稿件
AN - SCOPUS:85181834177
T3 - Proceedings of the 35th Chinese Control and Decision Conference, CCDC 2023
SP - 57
EP - 62
BT - Proceedings of the 35th Chinese Control and Decision Conference, CCDC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th Chinese Control and Decision Conference, CCDC 2023
Y2 - 20 May 2023 through 22 May 2023
ER -