Obstacle Avoidance With Dynamic Avoidance Risk Region for Mobile Robots in Dynamic Environments

Abstract

Uncertainty in dynamic environment increases complexity and difficulty in obstacle avoidance of robots. An avoidance method with dynamic obstacle avoidance risk region in a dynamic environment is proposed in this study. First, using the state estimation of the extended kalman filter, a dynamic obstacle avoidance risk region is constructed along the direction of the obstacle movement. Second, the robot's safe obstacle avoidance operation against dynamic obstacles combined with nonlinear model predictive control is realized. Finally, a series of experiments are used to verify the effectiveness of the proposed method. The experimental results showed that the robot can easily control its movement and a flat obstacle avoidance trajectory is obtained via the proposed method.