Decentralized Collision Avoidance Framework for Unmanned Aerial Vehicles
نویسندگان
چکیده
Collision avoidance for unmanned aerial vehicles (UAVs) is a vital issue when using multiple drones. Decentralized collision avoidance algorithms allow for greater range and independence when compared to a centralized approach; however, it also shifts the workload of detecting and resolving conflicts from a more powerful ground station onto individual agents, requiring both a computationally efficient algorithm and supporting framework. This paper presents a lightweight and modular decentralized collision avoidance framework for implementation on a low cost microcomputer. An existing distributed artificial potential field algorithm is modified for use with this framework. Finally, the effectiveness of this framework is verified in simulation and tested using real UAVs.
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تاریخ انتشار 2013