Autonomous Collision Avoidance for a Teleoperated UAV Based on a Super Ellipsoidal Potential Function
This thesis presents the design of a super ellipsoidal potential function (SEPF) that can be used, in a static and dynamic environment, for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3 dimensional space. In the design of the SEPF, we have the full control over the shape and size of the potential function. In our proposed approach, a teleoperated UAV can not only autonomously avoid collision with surrounding objects but also track the operator's control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high level guidance and navigation task without worrying too much about the UAV collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human in the loop simulation using virtual robot experimentation platform (v rep) and Matlab programs and experimentation using a physical quadrotor UAV in a laboratory environment.