A Collision Avoidance Strategy for Multirrotor UAVs Based on Artificial Potential Fields

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Abstract

Since some years, research on the use of unmanned aerial vehicles (UAVs) has been very popular, and because of that a wide range of commercial and military applications already exists. Nowadays, the trend towards autonomous flying is growing steadily. Autonomous flying requires UAVs to have the ability to navigate in urban or other challenging environments without causing collisions or endangering humans. To achieve this objective, a safe and reliable collision avoidance system (CAS) needs to be used. In particular, a CAS needs to successfully sense and detect a possible collision with an object to efficiently avoid the obstacle. Multiple different techniques exist to implement a CAS. In this paper, we propose a collision avoidance protocol which is based on magnetic attraction and repulsion forces. The results show that, with the use of our protocol, collisions are safely avoided in various scenarios, while maintaining the overhead time to a minimum.

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Van Der Veeken, S., Wubben, J., Calafate, C. T., Cano, J. C., Manzoni, P., & Marquez-Barja, J. (2021). A Collision Avoidance Strategy for Multirrotor UAVs Based on Artificial Potential Fields. In PE-WASUN 2021 - Proceedings of the 18th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (pp. 95–102). Association for Computing Machinery, Inc. https://doi.org/10.1145/3479240.3488531

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