A Mobile Robot Path Planning Method Based on Safe Pathfinding Guidance

The problem of path planning in the field of robot navigation is now a major research hot spot. On the premise of ensuring that the robot can successfully navigate to the target point, the safety of the path also needs to be considered. In order to find a safer path, a safe pathfinding path planning method is proposed, which introduces two safety parameters that affect the path selection: hazard coefficient and movement coefficient. After defining two security parameters, design an appropriate reward function and use A2C algorithm and PPO algorithm to guide the robot to conduct reinforcement learning. The experiment will be conducted on a two-dimensional grid map containing various obstacles. By conducting comparative experiments, it is verified that the safety pathfinding method proposed in this paper is feasible and reasonable, and can enable the robot to choose a safer road instead of a faster road when planning the path.