Design space exploration in hybrid control with RRT* and combined Artificial Potential Field methods for UAV obstacle avoidance

Recent advancements in Unmanned Aerial Vehicles (UAV) navigation systems are bringing the goal of fully autonomous missions closer. The development of safe navigation methods is a critical component in reaching this goal. In this work, we propose a hybrid navigation control method consisting of three layers: the deliberative layer which computes the path, avoiding obstacles using a global planner (RRT*) and smoothing the trajectory using B-splines; the execution layer; and the reactive control layer which employs the Artificial Potential Field (APF) method, enabling safe autonomous navigation in three-dimensional space. Two APF methods are combined in this work; the first incorporates the virtual force, while the other integrates the rotational force into the total repulsive force of the system. These enhancements aid in reaching the target more swiftly and prevent the system from becoming trapped in the local minimum. Finally, a design space exploration for the gain parameters of the attractive, repulsive, and rotational forces of the APF method is conducted, using the Uniform Latin Hypercube sampling, to find pair(s) of values that prevent the UAV from getting stuck to local minima and reducing the generated path length.