Navigation and guidance strategy online planning and execution for autonomous UAV

Unmanned Aerial Vehicles (UAVs) can nowadays, in certain conditions, be employed for different applications ranging from service robotics to surveillance applications in network monitoring or in search and rescue missions. For this aim, and for widening the UAV application field, it is mandatory for an UAV to have some capabilities for autonomous safe navigation in cluttered environments. This navigation capability includes environment mapping, localization and guidance functionalities relative to the environment. Especially, one can find intensive research work proposing different UAV relative localization and guidance solutions based on vision: visual odometry, visual SLAM (Simultaneous Localization and Mapping), visual servoing, etc. Such solutions can be embedded in the UAV onboard flight system as an alternative navigation function to the nominal ones (in most cases, the GPS/INS localization with the waypoint navigation). However, the decision of switching the navigation and guidance modes among those available onboard in function of the environment has not been studied much by the scientific community. In this context, the objective of this thesis is to develop an online planning approach to decide on the navigation and the guidance strategy, with which an UAV can fly to a goal in an efficient (minimum distance, minimum time) and safe (avoiding obstacles) way with its navigation capabilities. The output of such a planner will define a flight path along with the navigation and guidance modes to be used on each segment of the path.