Adversarial Obstacle Avoidance of a Multicopter by Nonlinear Receding Horizon Differential Game
Takumi Nagata, Kenta Hoshino, Toshiyuki Ohtsuka
This study applies a nonlinear receding horizon differential game (NRHDG) to control a multicopter to avoid an adversarial obstacle pursuing the multicopter in three-dimensional space. The multicopter determines its control inputs without prior knowledge of the obstacle’s control law. We propose a method for designing a performance index that takes into account the avoidance performance of the multicopter, and we verify its effectiveness through simulations of avoidance control against an approaching obstacle. For an adversarial obstacle approaching by proportional navigation, we show that the NRHDG, which assumes that the obstacle approaches according to a game optimal solution, has better avoidance performance than the nonlinear model predictive control, which assumes constant velocity linear motion of the obstacle.