A Robot Collision Avoidance Scheme Based on the Moving Obstacle Motion Prediction

Abstract

This paper proposes an integrated scheme for the robot to avoid collision based on obstaclepsilas motion prediction. The robot obtains the target bearing by using object detection technique and fuses the bearing information with the external sensors data to locate the current position of the moving target. The motion state of the moving obstacle is described using the constant velocity (CV) model, the constant accelerate (CA) model and the current statistical (CS) model. Then, a Kalman-based interacting multiple model (IMM) filter is adopted to estimate the obstacle motion trend. This scheme mainly focuses on the obstacle detection and the motion prediction. Based on the motion prediction of the obstacle, an abbreviated strategy is proposed for collision avoidance. To validate the proposed scheme, we have implemented an obstacle avoidance experiment with a Pioneer 3-AT robot and a moving obstacle. The results verify that the proposed scheme is valid and viable.