Obstacle avoidance with sensor uncertainty for small unmanned aircraft

The ability to detect, sense, and avoid obstacles in the environment is a critical capability for autonomous groups of unmanned aircraft. The overall obstacle avoidance problem is typically studied as two or three separate subproblems. Unfortunately, such an approach can lead to unrealistic assumptions being made about the other subsystems or specification of unnecessarily high levels of subsystem performance. In this paper, we present an approach to obstacle avoidance in the context of a multilayered, multi-objective control architecture that considers both the aircraft dynamics and sensor limitations in an integrated framework. Specifically, the concept of reachable sets is extended to include the error model of parallel-baseline, stereovision. An analytical solution is presented for the planar motion of a single unmanned aircraft. In addition, the extension to groups of UAV is introduced.