Moving Obstacle Avoidance Using MPPI Based on Cost Maps Considering Velocity and Predicted Poses

In this paper, we propose a method of motion planning using MPPI based on obstacle cost maps, to realize stable avoidance behavior for moving obstacles. The proposed method creates cost maps considering moving obstacles, and performs motion planning based on cost function formulation with MPPI. In cost map creation, we propose a cost shape that takes into account velocity and predicted poses of moving obstacles. In motion planning, we adopt MPPI which is one of the mainstream sampling-based methods. To apply cost maps to MPPI, we formulate cost functions of MPPI that appropriately avoid obstacles. In simulation experiments, we performed moving obstacle avoidance in an environment with 50 pedestrians, and our proposed method achieved the highest success rate (94%). Our method realized stable avoidance behavior for moving obstacles even in crowded environments, by creating cost maps considering velocity and predicted poses of moving obstacles, and performing motion planning based on these maps using MPPI.