Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 28, 2023 - July 01, 2023
Recently, Model Predictive Path Integral (MPPI) control algorithm has been applied to autonomous navigation tasks. However, using the conventional MPPI algorithm for the autonomous navigation of a quadrotor, there are cases in which a quadrotor cannot stay around a target position or avoid a concave-shaped obstacle. In this paper, we propose two algorithms to solve those problems. The first one is the noise variance control algorithm. This algorithm controls the variance of noise added for sampling depending on the distance between the position of a quadrotor and the target position. The second one is the unapproachable point algorithm. This algorithm creates an unapproachable point if a quadrotor stays in the same position for a while because of unable to avoid an obstacle. An unapproachable point gives a cost depending on the distance from the current position of a quadrotor to keep the quadrotor apart from the unapproachable point. We implemented those two algorithms on simulations and found that the quadrotor can avoid concave-shaped obstacles and stay around the given target position.
