VELOCITY BASED POTENTIAL FIELD METHOD FOR COLLISION AVOIDANCE OF AUTONOMOUS AERIAL VEHICLES
Sagar Lakhmani · 2018
The projected increase in the number of uninhabited air vehicles (for civilian applications such as package delivery and emergency response) and the potential rise of personal air vehicles means that the airspace will become very crowded. Safely managing these aircraft will require scalable, safe methods for collision avoidance. The primary focus of this thesis is to develop a method which is scalable to multiple vehicles and can be implemented in real time. State-of-the-art techniques for obstacle avoidance produce good results with static obstacles. However, with the increase in the number of vehicles and dynamic obstacles, the complexity of these algorithm increases. This makes these algorithms impractical for online implementation. The thesis proposes a velocity based approach derived from potential fields for obstacle avoidance. It uses the velocity of the aerial vehicles to generate a spherical safe zone around the vehicle. Other vehicles (which act as dynamic obstacles) get repelled by the safe zone. Given the vehicles are able to follow the commanded velocities, the vehicles will safely reach their goal location. The method is first implemented in simulation and scalability is tested for around 50 vehicles at a time. Then, the approach is tested in an indoor environment with multiple UAVs trying to avoid each other. Results for both simulation and physical experiments are presented. Parameters such as separation distance, closest approach, and the number of collisions are used to demonstrate the feasibility of this approach.