Planning Algorithms
Flying Insects and Robots
Computer Vision and Action Recognition: A Guide for Image Processing and Computer Vision Community for Action Understanding
Translational and Rotational Damping of Flapping Flight and Its Dynamics and Stability at Hovering
IEEE Transactions on Robotics
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The power, size, and weight constraints of micro air vehicles (MAVs) limit their on-board sensing and computational resources. Ground vehicles have less mobility than MAVs, but relaxed size constraints, and typically more computing power. These specializations present many opportunities for robot-robot cooperation. In this work, we demonstrate cooperative target-seeking between a 13 gram ornithopter MAV and a lightweight ground station using computer vision. We develop models for the ornithopter, ground station, and cooperative system dynamics. We determine model parameters of the real systems through experimental system identification. Finally, we verify those models using experiments on narrow passage traversal, and arrive at a cooperative system model which accurately predicts the backwards-reachable region for successfully negotiating ornithopter flight through narrow passages. We also introduce a new ornithopter MAV, the 13 gram H2Bird. It features clap and fling wings, improves upon previous designs by utilizing a carbon fiber airframe, tail rotor, and elevator, and carries a 2.8 gram payload. We augment the ornithopter's built-in gyroscope-based control with a lightweight ground station, which has power and weight requirements appropriate for deployment on ground vehicles with 10 gram payloads. The ground station provides heading estimates to the ornithopter by running a real-time motion tracking algorithm over a live video stream.