I found in my archives an interesting research paper by Andrew J. Barry. It was published for ICRA 2015
He made an autonomous obstacle avoidance algorithm using stero-vision which can be run on “cheap” hardware.
We present a novel stereo vision algorithm thatis capable of obstacle detection on a mobile ARM processorat 120 frames per second. Our system performs a subset ofstandard 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 otherdepths, building and updating a local depth-map at framerate. Here, we describe both the algorithm and our implementation on a high-speed, small UAV, flying at over 20 MPH (9m/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.
The technical video is available here.
The paper can be read here.
And the code is available here
Note: He is now working on Boston Dynamics. We can infer similar algorithms could be used for their robot in order to avoid using a LIDAR.