Motion Planning of Rope Driven Snake Manipulator for Aircraft Fuel Tank Inspection Based on Ant Colony Optimization

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.