Hybrid path planning for nonholonomic mobile robot based on steering control and improved distance propagating

A hybrid path planner combining global optimization and quick obstacle avoidance is proposed for nonholonomic mobile robot path planning in partially known environments. This method can not only effectively plan a global optimal path using the prior environment information, but also quickly avoid the unknown obstacles based on the laser scanning. Using grid point sequence to represent the workspace, a global path planner based on the improved distance propagating method can generate a series of sub-goal-points to the target which are far from the obstacles. According to the information of the laser scanning, the steering control method is used as the local path planner to implement real-time obstacle avoidance. Experiment results in the clustered indoor scenes show the method's effectiveness and practicability