Fuzzy Collision Avoidance Algorithm for UAVs
- Dr. James Crowder, CAES APD
Dr. John Carbone, Dept of Electrical and Computer Engineering, Southern Methodist University
Multi-vehicle, multi-route conflict (collision) avoidance is an issue that will become prevalent over the next decade. With the dramatic increase in the number of UAV drones and number of separate companies planning to employ UAVs for everything from aerial reconnaissance to delivery to search and rescue operations, understanding how to simply and effectively keep UAVs from coming in conflict with each other is a major concern. One of the issues associated with conflict avoidance is to not have to tax the computational, memory, and energy usage of the UAV to employ a conflict resolution strategy. Here we present a fuzzy-based algorithm for detection and implementation of conflict avoidance for UAVs/ drones that will not adversely affect the power, weight, or size of the individual units.
What we propose is a simple, fuzzy logic-driven algorithm for collision/conflict avoidance for UAVs or small drones. The use of a random, fuzzy-based algorithm allows for fast, efficient computation. There would be a software agent on the drones/UAVs that would manage the collision/conflict avoidance system and send information to the flight control system for speed/directional change, depending on the output of the collision/conflict avoidance algorithms. Included will be a discussion of the ISCAN© radar system capable of implanting these algorithms on small drones.
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