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Front Neurosci. 2014 Jan 17;7:275. doi: 10.3389/fnins.2013.00275. eCollection 2013.

Adaptive pulsed laser line extraction for terrain reconstruction using a dynamic vision sensor.

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Department of Information Technology and Electrical Engineering, Institute of Neuroinformatics, ETH Zurich and University of Zurich Zurich, Switzerland.
Autonomous Systems Lab, Department of Mechanical and Process Engineering, ETH Zurich Zurich, Switzerland.


Mobile robots need to know the terrain in which they are moving for path planning and obstacle avoidance. This paper proposes the combination of a bio-inspired, redundancy-suppressing dynamic vision sensor (DVS) with a pulsed line laser to allow fast terrain reconstruction. A stable laser stripe extraction is achieved by exploiting the sensor's ability to capture the temporal dynamics in a scene. An adaptive temporal filter for the sensor output allows a reliable reconstruction of 3D terrain surfaces. Laser stripe extractions up to pulsing frequencies of 500 Hz were achieved using a line laser of 3 mW at a distance of 45 cm using an event-based algorithm that exploits the sparseness of the sensor output. As a proof of concept, unstructured rapid prototype terrain samples have been successfully reconstructed with an accuracy of 2 mm.


address-event representation (AER); dynamic vision sensor (DVS); event-based; neuromorphic; robotics; silicon retina

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