Location, Planning and Control Algorithm of a Novel Magnetic Adhesion Wheel Robot

doi:10.3901/JME.2025.21.060

Abstract

Abstract: The containment vessel of a nuclear power plant is regarded as the last line of defense and plays a crucial role in safety. Traditional manual inspection of weld seams is considered inefficient and poses certain risks. Therefore, the replacement of manual weld seam inspection with robots is endowed with significant practical significance. A systematic study is conducted on the positioning, path planning, and control of magnetically adsorbed wheeled robots in complex wall environments. Firstly, based on the structural configuration of the magnetically adsorbed wheeled robot, a positioning algorithm utilizing the robot's internal sensors is proposed. An enhanced genetic algorithm is designed for weld seam traversal path planning by integrating weld distribution mapping and driving torque metrics, demonstrating superior performance in path smoothness and energy efficiency compared to the conventional Fleury algorithm. To address limitations of fixed magnetic adsorption forces, a dynamic adsorption force control strategy is developed through an improved deep deterministic policy gradient (DDPG) algorithm. A simulation environment is constructed using MuJoCo, Gym, and PyTorch frameworks, where motor feedback control algorithms are validated and robot movements under varying adsorption forces are simulated. The optimized DDPG algorithm is employed to formulate a dynamic magnetic force regulation strategy that ensures adequate adhesion while minimizing energy consumption and enhancing stability. A weld seam recognition algorithm based on the YOLOv8 architecture is proposed and experimentally validated through prototype testing. Finally, YOLOv8’s superior performance is confirmed, leading to its deployment on the robotic system after model training. Finally, YOLOv8 was selected as the weld-seam detection algorithm and the trained model was deployed on the robot. The research results provide an efficient, low-risk, and intelligent solution for the safe operation and maintenance of ferromagnetic structures such as nuclear power plant containments, large storage tanks, and ship hulls. The work serves as an important demonstration for advancing robotic inspection and maintenance in China’s nuclear, petrochemical, and shipbuilding industries, and holds significant potential for wide industrial adoption.

Key words: magnetic adhesion robot, ergodic path planning, deep deterministic policy gradient algorithm, magnetic adhesion force control, weld identification

CLC Number:

TH112

LI Tongjia, ZANG Pengxiang, GUO Weizhong. Location, Planning and Control Algorithm of a Novel Magnetic Adhesion Wheel Robot[J]. Journal of Mechanical Engineering, 2025, 61(21): 60-74.

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