Fuzzy Gain Scheduling of Artificial Potential Fields for Online Path Planning and Obstacle Avoidance of an Aerial Robot

In this research, the performance of the traditional artificial potential field (TAPF) method in online path planning & obstacle avoidance of an aerial robot has been improved. In the TAPF method, the attraction coefficient of the target field and the repulsion coefficient of the obstacle fields are constant, which due to the agile dynamics of aerial robots may cause problems such as hitting an obstacle, missing the target with a long distance, and the path fluctuation when passing through narrow paths. The fuzzy artificial potential field (FAPF) method was presented to solve the mentioned problems. This method determines artificial potential field coefficients online using fuzzy logic. This fuzzy logic schedules artificial potential field coefficients by considering the distance and the line-of-sight angle between the UAV and target/obstacle. The simulation results show the performance and efficiency of the FAPF compared with the TAPF in the path planning problem.