RRT* Combined with GVO for Real-time Nonholonomic Robot Navigation in Dynamic Environment

Challenges persist in nonholonomic robot navigation for dynamic environments. This paper presents a framework for nonholonomic robot navigation in dynamic environment based on the model of Generalized Velocity Obstacles (GVO). The idea of velocity obstacles has been well studied and developed for obstacle avoidance since proposed in 1998. Though proved to be successful, most studies assume equations of motion to be linear, which limit the application to holonomic robots. In addition, more attention has been paid to the immediate reaction of robots while advance planning has always been ignored. By applying GVO model to differential drive robots and combining it with RRT*, we reduce the uncertainty of robot trajectory, thus further reduce the concerned range, and save both computation time and running time. By introducing uncertainty for the dynamic obstacles by Kalman filter, we reduce the risk of considering obstacles to uniformly move along a straight line and guarantee the safety. Special concern has been given to the path generation, including curvature check, making the generated path feasible for nonholonomic robots. We experimentally demonstrated the feasibility of the framework.