Simulation of autonomous UAV navigation with collision avoidance and spatial awareness.

The goal of this thesis is to design a collision-free autonomous UAV navigation system with spatial awareness ability within a comprehensive simulation framework. The navigation system is required to find a collision-free trajectory to a randomly assigned 3D target location without any prior map information. The implemented navigation system contains four main components: mapping, localisation, cognition and control system, where the cognition system makes execution command based on the perceived position information about obstacles and UAV itself from mapping and localisation system respectively. The control system is responsible for executing the input command made from the cognition system. The implementation for the cognition system is split into three case studies for real-life scenarios, which are restricted area avoidance, static obstacle avoidance and dynamic obstacles. The experiment results in the three cases have been conducted, and the UAV is capable of determining a collision-free trajectory under all three cases of environments. All simulated components were designed to be analogous to their real-world counterpart. Ideally, the simulated navigation framework can be transferred to a real UAV without any changes. The simulation framework provides a platform for future robotic research. As it is implemented in a modular way, it is easier to debug. Hence, the system has good reliability. Moreover, the system has good readability, maintainability and extendability.