Micro air vehicle autonomous obstacle avoidance from stereo vision
We introduce a new approach for on board autonomous obstacle avoidance for micro air vehicles flying outdoors in close proximity to structure. Our approach uses inverse range, polar perspective stereo disparity maps for obstacle detection and representation, and deploys a closed loop RRT planner that considers flight dynamics for trajectory generation. While motion planning is executed in 3D space, we reduce collision checking to a fast z buffer like operation in disparity space, which allows for significant speed up compared to full 3d methods. Evaluations in simulation illustrate the robustness of our approach, whereas real world flights under tree canopy demonstrate the potential of the approach.
Defense Security Symposium