Autonomous Trajectory Planning Using Real-Time Information Updates

Abstract

We present a dynamic optimal control method for autonomous trajectory planning and control of an Unmanned Ground Vehicle (UGV) using real-time information updates. The objective of the UGV is to traverse from an initial start point and reach its goal in minimum time, with maximum robustness, while avoiding both static and dynamic obstacles. This is achieved by deriving the control solution that carries out the initial planning problem while minimizing a cost and satisfying constraints based on the initial global knowledge of the area. To combat the problem of inaccurate global knowledge and a dynamic environment, the UGV uses its sensors to map the locally detected change in the environment and continuously updates its global map to re-compute a control solution that can achieve an optimal trajectory to the goal. Simulation results illustrate successful implementation of the method in various scenarios.