Abstract: Aiming at the problem that  traditional obstacle avoidance search algorithms could only solve single-point distribution and inadequately considered  the needs for multi-point distribution and round-trip pickups in workshop material distribution, we proposed an A* algorithm that combined  a genetic algorithm optimization. This method employed the cost calculation approach of the A* algorithm to complete cost calculation between various distribution points under obstacle conditions, and integrated 
the iterative optimization characteristics of the genetic algorithm to achieve efficient and stable global search for multi-point distribution and round-trip pickup requirements. Through the verification of a practical example of material distribution in a certain workshop, the improved algorithm can effectively plan distribution paths in obstacle environments and  significantly improve distribution efficiency.

Key words: path planning, material distribution, genetic algorithm, A* algorithm, grid environment