Watch: MIT Drone Autonomously Avoids Obstacles at 30 MPH

The software runs 20 times faster than current solutions and maps the drone's environment in real time.

Photo Caption: In-flight snapshot of single-disparity stereo detections on a goalpost (blue boxes) and past detections integrated through the state estimate and reprojected back on the image (red dots). Overlay includes relevant flight data such as airspeed in MPH (left) and altitude in feet (right). (Credit: Andrew Barry/MIT CSAIL)

Barry wrote about the system in his paper “Pushbroom Stereo for High-Speed Navigation in Cluttered Environments” (PDF) and says he needs to improve the software so it can work at more than one depth and dense environments.

“Our current approach results in occasional incorrect estimates known as ‘drift,’” he says. “As hardware advances allow for more complex computation, we will be able to search at multiple depths and therefore check and correct our estimates. This lets us make our algorithms more aggressive, even in environments with larger numbers of obstacles.”

So what’s the significance of all this? Well, if this technology was built into drones, they wouldn’t be able to crash into things, such as powerlines in West Hollywood that caused 650 people to be without power for three hours. But if Amazon, Google, Walmart and others want to drones to deliver products to customers, the drones can’t be crashing into things. It could also help hobbyists from destroying their drones.

MIT also recently tested a new system that combines simple control programs to enable fleets of drones to collaborate in unprecedented ways. MIT figured out how to sync the actions of multiple robots working in the same space, testing the concept on a small group of delivery drones. The drones need to cross paths to make the deliveries, obviously without crashing. Before they fly, the drones map out the optimal flight path and the Dec-POMDPs take over to aid the collaboration.




About the Author

Steve Crowe · Steve Crowe is managing editor of Robotics Trends. Steve has been writing about technology since 2008. He lives in Belchertown, MA with his wife and daughter.
Contact Steve Crowe: scrowe@ehpub.com  ·  View More by Steve Crowe.




Comments

DroneZon · January 3, 2017 · 3:31 pm

Nice article indeed. In 2016 we seen a few drones coming to the market with collision avoidance. Yuneec Typhoon H using Intel RealSense technology and DJI Phantom 4 using Vision / Ultrasonic sensors for obstacle detection and avoidance.  So for 2017 we should see many more collision avoidance drones coming on the market.


DroneZon · January 3, 2017 at 3:31 pm

Nice article indeed. In 2016 we seen a few drones coming to the market with collision avoidance. Yuneec Typhoon H using Intel RealSense technology and DJI Phantom 4 using Vision / Ultrasonic sensors for obstacle detection and avoidance.  So for 2017 we should see many more collision avoidance drones coming on the market.


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