Navigation of a Quadrotor Based on Voronoi Division Calculated from Local Information

This study applies a successful collision-avoidance method using buffered Voronoi cells (BVC) to control quadrotors. In particular, we consider the case of dealing with stationary obstacles using only the local information obtained from sensors, which has not been discussed in previous studies. In this study, we assume an unknown environment with grid-shaped obstacles. We demonstrate that four quadrotors can compute the information required for the BVC-based collision avoidance algorithm and move in the same environment without communicating with each other or receiving information from a central controller, using the local information obtained from the mounted 3D LiDAR. Simulations indicate that the system can handle static obstacles using point-cloud data obtained using 3D LiDAR as Voronoi seeds. We also demonstrate that the BVC-based collision avoidance algorithm can be applied to quadrotors controlled by a simple PD position controller without any modification to the controller. These findings show that the BVC-based collision avoidance can be easily implemented using existing commercial drones.