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Proceedings Paper

Auto-preview camera orientation for environment perception on a mobile robot
Author(s): Micho Radovnikovich; Pavan K. Vempaty; Ka C. Cheok
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Paper Abstract

Using wide-angle or omnidirectional camera lenses to increase a mobile robot's field of view introduces nonlinearity in the image due to the 'fish-eye' effect. This complicates distance perception, and increases image processing overhead. Using multiple cameras avoids the fish-eye complications, but involves using more electrical and processing power to interface them to a computer. Being able to control the orientation of a single camera, both of these disadvantages are minimized while still allowing the robot to preview a wider area. In addition, controlling the orientation allows the robot to optimize its environment perception by only looking where the most useful information can be discovered. In this paper, a technique is presented that creates a two dimensional map of objects of interest surrounding a mobile robot equipped with a panning camera on a telescoping shaft. Before attempting to negotiate a difficult path planning situation, the robot takes snapshots at different camera heights and pan angles and then produces a single map of the surrounding area. Distance perception is performed by making calibration measurements of the camera and applying coordinate transformations to project the camera's findings into the vehicle's coordinate frame. To test the system, obstacles and lines were placed to form a chicane. Several snapshots were taken with different camera orientations, and the information from each were stitched together to yield a very useful map of the surrounding area for the robot to use to plan a path through the chicane.

Paper Details

Date Published: 18 January 2010
PDF: 8 pages
Proc. SPIE 7539, Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques, 75390Q (18 January 2010); doi: 10.1117/12.839139
Show Author Affiliations
Micho Radovnikovich, Oakland Univ. (United States)
Pavan K. Vempaty, Oakland Univ. (United States)
Ka C. Cheok, Oakland Univ. (United States)

Published in SPIE Proceedings Vol. 7539:
Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

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