Pushbroom Stereo for High-Speed Navigation in Cluttered Environments
This enables small UAVs to navigate cluttered environments autonomously at high speeds, though it is incremental as it builds on existing stereo methods.
They tackled obstacle detection for high-speed UAV navigation by developing a stereo vision algorithm that runs at 120 fps on a mobile CPU, enabling flight at over 20 MPH near obstacles without external sensing.
We present a novel stereo vision algorithm that is capable of obstacle detection on a mobile-CPU processor at 120 frames per second. Our system performs a subset of standard block-matching stereo processing, searching only for obstacles at a single depth. By using an onboard IMU and state-estimator, we can recover the position of obstacles at all other depths, building and updating a full depth-map at framerate. Here, we describe both the algorithm and our implementation on a high-speed, small UAV, flying at over 20 MPH (9 m/s) close to obstacles. The system requires no external sensing or computation and is, to the best of our knowledge, the first high-framerate stereo detection system running onboard a small UAV.