A Study on Path Planning Using Bi-Directional PQ-RRT* Algorithm and Trajectory Tracking Technique Using Incremental Backstepping Control

An autonomous flight system is essential for effective mission performance of UAVs, which are increasingly being applied in civil and military missions. Thus, in this study, an effective approach for implementing guidance and flight control systems is proposed. Based on the rapidly-exploring random tree (RRT) algorithm, the bidirectional potential quick (PQ)-RRT* is proposed to implement the path planner of the guidance system. The proposed bidirectional PQ-RRT* algorithm has a combination of three different types of improvement methods based on RRT*: potential field guided sampling (P-RRT*), modified RRT*(Q-RRT*), and bi-directional searching tree methods (Bi-RRT*). The convergence path was efficiently optimized using the line-of-sight path optimization algorithm. Then, a flyable trajectory was generated by a 7^th order spline generator with waypoints from the path planner. Finally, incremental backstepping control was adopted to ensure trajectory-tracking performance within the overall operational flight envelope. To validate a series of processes, a simulation was performed to examine the practical realization. Based on the results, the bidirectional PQ-RRT* and line-of-sight path optimization algorithms were validated to provide an effective solution. In addition, the proposed flight control system exhibited excellent trajectory-tracking performance.