PSEUDOSPECTRAL OPTIMAL CONTROL ALGORITHM FOR REAL-TIME TRAJECTORY PLANNING

We present the development and implementation of a new pseudospectral (PS) optimal control-based algorithm for autonomous trajectory planning and control of an Unmanned Ground Vehicle (UGV) with real-time information updates. The basic algorithm is presented and used to solve a dynamic trajectory planning problem. The UGV mission is to traverse from an initial start point and reach the target point 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. The control solution is repeatedly recomputed and updated throughout the vehicle's mission. To combat the problem of inaccurate global knowledge and/or a dynamic environment, the UGV uses its sensors to map the locally detected changes in the environment and continuously updates its global map before re-computing the next control solution that can achieve an optimal trajectory to the goal. We present the complete algorithm and its successful implementation through various scenarios.