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The International Journal of Robotics Research
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Flying Fast and Low Among Obstacles: Methodology and Experiments

Sebastian Scherer

Carnegie Mellon University - The Robotics Institute 5000 Forbes Ave Pittsburgh, PA 15213 USA, basti{at}andrew.cmu.edu

Sanjiv Singh

Carnegie Mellon University - The Robotics Institute 5000 Forbes Ave Pittsburgh, PA 15213 USA, ssingh{at}ri.cmu.edu

Lyle Chamberlain

Carnegie Mellon University - The Robotics Institute 5000 Forbes Ave Pittsburgh, PA 15213 USA, lylesjazz{at}gmail.com

Mike Elgersma

Honeywell Labs, Camden, Mike.Elgersma{at}honeywell.com

Safe autonomous flight is essential for widespread acceptance of aircraft that must fly close to the ground. We have developed a method of collision avoidance that can be used in three dimensions in much the same way as autonomous ground vehicles that navigate over unexplored terrain. Safe navigation is accomplished by a combination of online environmental sensing, path planning and collision avoidance. Here we outline our methodology and report results with an autonomous helicopter that operates at low elevations in uncharted environments, some of which are densely populated with obstacles such as buildings, trees and wires. We have recently completed over 700 successful runs in which the helicopter traveled between coarsely specified waypoints separated by hundreds of meters, at speeds of up to 10 m s—1 at elevations of 5—11 m above ground level. The helicopter safely avoids large objects such as buildings and trees but also wires as thin as 6 mm. We believe this represents the first time an air vehicle has traveled this fast so close to obstacles. The collision avoidance method learns to avoid obstacles by observing the performance of a human operator.

Key Words: Aerial robotics • learning

The International Journal of Robotics Research, Vol. 27, No. 5, 549-574 (2008)
DOI: 10.1177/0278364908090949
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