Implementation of an Optimal System for the Detection and Avoidancesystem on an Unmanned Aircraft System
Remotely Piloted Aircraft System (RPAS) will be essential in developing and monitoring Canada’s territories. This is in part due to a lack of suitable human pilots due to skill shortages and difficult conditions making recruitment difficult; there are also “dull, dirty and dangerous” aspects of the missions that make a remote pilot operation safer. Miniaturization, machine learning and robotics are all fields which may contribute to overcoming these challenges in new and affordable ways. In this research project, we propose to research and implement an obstacle avoidance system which allows the unmanned aircraft to detect and avoid flying obstacles using an air-to-air radar setup.