Utilizing the RRT*-Algorithm for Collision Avoidance in UAV Photogrammetry Missions
This addresses safety and efficiency for drone operators in mapping missions, but it is incremental as it adapts an existing algorithm to a specific application.
The paper tackled collision avoidance for UAVs in photogrammetry missions by applying the RRT* algorithm, achieving successful obstacle avoidance at speeds up to 6 m/s.
This paper presents the application of the Rapidly-exploring Random Tree Star (RRT*) algorithm for multicopter collision avoidance in photogrammetry missions. For better applicability, the presented algorithm redirects the drone onto a predefined mission's path. The experiments are conducted in the simulation software gazebo utilizing a ROS interface to the widely known autopilot software PX4. For obstacle detection, a simulated Intel D435 stereo camera is used. The experiments include two different scenarios, each conducted with two different maximum velocities. The results show that the probabilistic RRT*-algorithm can avoid obstacles successfully and intelligibly even at speeds up to 6 m/s. The main problems persist in the dynamic behavior, the inertia of the multicopter, and the limitations of the sensor technology.