High-speed navigation in cluttered environments, Robot Locomotion Group, CSAIL, Cambridge, Massachusetts, USA

[Airicist]

Developer - Robot Locomotion Group

Team:

Russ Tedrake

Andrew Barry

[Airicist]

Article "Pushbroom Stereo for High-Speed Navigation in Cluttered Environments"

by Andrew J. Barry and Russ Tedrake

Article "Fast Onboard Stereo Vision for UAVs"

by Andrew J. Barry, Helen Oleynikova, Dominik Honegger, Marc Pollefeys and Russ Tedrake

[Airicist]

Fast and Accurate Knife-Edge Maneuvers for Autonomous Aircraft

Published on Jun 20, 2012

We have built a computer-controlled aircraft that flies accurately enough to navigate safely through a gap that is smaller than its wingspan. We demonstrate multiple flights of this vehicle with on-board camera footage and high-speed video.

Work by:
Andrew Barry, Anirudha Majumdar, Tim Jenks, and Russ Tedrake

Robot Locomotion Group
Computer Science and Artificial Intelligence Lab
Massachusetts Institute of Technology

[Airicist]

Pushbroom stereo for high-speed navigation in cluttered environments

Published on Oct 7, 2014

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Planning and Control for Quadrotor Flight through Cluttered Environments

Published on May 27, 2015

Benoit Landry
Robot Locomotion Group
MIT CSAIL

Previous demonstrations of autonomous quadrotor flight have typically been limited to sparse environments due to the computational burden associated with planning for a large number of obstacles. We hypothesized that it would be possible to do efficient planning and robust execution in obstacle-dense environments using the novel Iterative Regional Inflation by Semidefinite programming algorithm (IRIS), mixed- integer semidefinite programs (MISDP), and model-based control approaches. Here, we present experimental validation of this hypothesis using a small quadrotor in a series of indoor environments including a cubic meter volume containing 20 interwoven strings. We chose one of the smallest hardware platforms available on the market (34g, 92mm rotor to rotor), allowing for these dense environments and explain how to overcome the many system identification, state estimation, and control problems that result from the small size of the platform and the complexity of the environments.

Code available at github.com/blandry/crazyflie-tools

Planning and navigation for drone flight

Published on Jan 19, 2016

[Airicist]

Drone autonomously avoiding obstacles at 30 MPH

Published on Nov 2, 2015