Situation Aware Trajectory Tracking for Micro Air Vehicles in Obstacle Rich Environments
Andrew Berry, J. Howitt, Ian Postlethwaite, Dongbing Gu · 2009
When operating unmanned vehicles within complex, obstacle rich, environments there is a need to consider continually the local obstacle space, even when tracking a trajectory designed with that space in mind. Disturbances such as gusts, of particular importance to micro air vehicles, inevitably lead to trajectory tracking errors which in turn require trajectory re-acquire manoeuvres that must be conducted with an awareness of the surrounding obstacle space. Additionally, there will exist a class of unmapped or dynamic obstacles that will require en-route detection, but which can be handled intuitively without impacting on large scale or global plan. The work discussed in this paper is aimed at handling this class of obstacle and disturbance by providing trajectory tracking algorithms with a ‘situation awareness’. This is done by creating a continuous local motion planning layer, that sits between a global (or large scale) planner and the vehicle autopilot. This local motion planning layer is implemented as a constrained optimisation problem, combining: (i) Vehicle Performance Limits, (ii) Local Obstacle Information & (iii) Environmental Conditions, into a receding horizon framework that continuously designs safe and dynamically feasible local trajectories.