TY - GEN
T1 - Motion Planning of Rope Driven Snake Manipulator for Aircraft Fuel Tank Inspection Based on Ant Colony Optimization
AU - Zhu, Xiao
AU - Gu, Haiyu
AU - Ma, Liang
AU - Zhao, Yang
AU - Wei, Cheng
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The narrow and confined structure of aircraft fuel tanks presents significant challenges and risks in manual inspection. In response, the Rope Driven Snake Manipulator (RDSM), noted for its high redundancy and slender structure, is progressively integrated into aviation field as an auxiliary aid. Due to the constrained access and internal obstacles like straps and baffles, optimal pathfinding for RDSM is required to navigate effectively and avoid obstacles, placing considerable demands on motion planning. First, the mechanism and kinematic model of RDSM are established according to the fuel tank structure. Then, a novel algorithm merging Ant Colony Optimization (ACO) with the artificial potential field method for path planning is proposed. Bio-inspired motion tracking control is utilized for validation through simulation and experimentation. The results demonstrate that this algorithm offers computational efficiency and enhanced accuracy, achieving error control at the millimeter level.
AB - The narrow and confined structure of aircraft fuel tanks presents significant challenges and risks in manual inspection. In response, the Rope Driven Snake Manipulator (RDSM), noted for its high redundancy and slender structure, is progressively integrated into aviation field as an auxiliary aid. Due to the constrained access and internal obstacles like straps and baffles, optimal pathfinding for RDSM is required to navigate effectively and avoid obstacles, placing considerable demands on motion planning. First, the mechanism and kinematic model of RDSM are established according to the fuel tank structure. Then, a novel algorithm merging Ant Colony Optimization (ACO) with the artificial potential field method for path planning is proposed. Bio-inspired motion tracking control is utilized for validation through simulation and experimentation. The results demonstrate that this algorithm offers computational efficiency and enhanced accuracy, achieving error control at the millimeter level.
KW - ACO
KW - Artificial potential field method
KW - Bionic following
KW - Kinematic model
KW - RDSM
UR - https://www.scopus.com/pages/publications/105012024369
U2 - 10.1109/MEAE62008.2024.11026439
DO - 10.1109/MEAE62008.2024.11026439
M3 - 会议稿件
AN - SCOPUS:105012024369
T3 - 2024 10th Asia Conference on Mechanical Engineering and Aerospace Engineering, MEAE 2024
SP - 1710
EP - 1714
BT - 2024 10th Asia Conference on Mechanical Engineering and Aerospace Engineering, MEAE 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th Asia Conference on Mechanical Engineering and Aerospace Engineering, MEAE 2024
Y2 - 18 October 2024 through 20 October 2024
ER -