Aiming at the problems of long path length and numerous turning points of jump point search (JPS) algorithm and path tortuosity with low pathfinding efficiency of path finding caused by artificial potential field (APF) falling into U-shaped trap in complex U-shaped obstacle environment. this paper proposes a mobile robot path planning algorithm that integrates an improved JPS algorithm and APF algorithm (JPS*-APF). Firstly, an angle deviation function is introduced into traditional JPS algorithm, and redundant nodes are removed to reduce search distance and turning frequency. Secondly, turning points from improved JPS algorithm are used as sub-goals, guiding APF algorithm in segments to escape U-shaped trap. Adaptive generation of repulsive forces for corner obstacles or dynamic sub-goals enhances path smoothness. Then, symmetric virtual obstacles are added to the target area to resolve target inaccessibility, while external repulsive forces and re-planning strategies are fused to escape local optima and improve pathfinding efficiency. Finally, relative velocity repulsive forces are introduced to ensure safety during dynamic obstacle avoidance. Numerical simulations in different U/L-shaped obstacle environments demonstrate that JPS*-APF algorithm reduces pathfinding time by an average of 51.5% and path length by 7.3% compared to IA*-APF algorithm. Moreover, JPS*-APF algorithm generates smoother paths, effectively escapes U-shaped traps, and enhances mobile robot’s working efficiency. The feasibility of JPS*-APF algorithm is also validated through real-world experimental tests.