TY - GEN A1 - Archila, Oscar F. A1 - Wouwer, Alain Vande A1 - Schiffer, Johannes T1 - A multiple artificial potential functions approach for collision avoidance in UAV systems T2 - IEEE transactions on intelligent transportation systems N2 - Collision avoidance is a problem largely studied in robotics, particularly in uncrewed aerial vehicle (UAV) applications. The main challenges in this area are hardware limitations, the need for rapid response, and the uncertainty associated with obstacle detection. Artificial potential functions (APOFs) are a prominent method to address these challenges. However, existing solutions lack assurances regarding closed-loop stability and may result in chattering effects. Hence, we propose a high-level control method for static obstacle avoidance based on multiple artificial potential functions (MAPOFs), with a set of switching rules with conditions on the parameter tuning ensuring the stability of the final position. The stability proof is established by analyzing the closed-loop system using tools from hybrid systems theory. Furthermore, we validate the performance of the MAPOF control through simulations and real-life experiments, showcasing its effectiveness in avoiding static obstacles. KW - Artificial potential functions KW - Collision avoidance KW - Switched system KW - Uncrewed aerial vehicle (UAV) Y1 - 2025 U6 - https://doi.org/10.1109/TITS.2025.3579157 SN - 1524-9050 VL - 26 IS - 10 SP - 16688 EP - 16699 PB - IEEE CY - New York, NY ER -