Objective Path planning for rescue robots in chemical parks is a hot topic in current research. To address the issues of traversing redundant nodes high memory consumption and slow computation speed of the traditional A* algorithm in rescue robot path planning an improved A* algorithm is proposed. Methods An adaptive weight evaluation function is designed to dynamically adjust the actual cost so as to enhance the algorithm?? s efficiency and convergence speed. The jump point search strategy JPS is employed to screen jump points reducing memory consumption and node estimation. A cubic uniform B-spline curve is used to process the optimized path to improve the stability and feasibility of the rescue robot?? s movement. Results The path planning problem of the rescue robot is simulated by constructing a Unity3D simulation scene in the chemical park and the simulation results show that the improved A* algorithm exhibits high efficiency and accuracy. Conclusion This algorithm offers a more efficient and intelligent solution for the path planning of rescue robots in chemical parks meeting the requirement for rapid path planning in such areas.