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Fusing Ladar and Color Image Information for Mobile Robot Feature Detection and Tracking

Published

Author(s)

Tsai Hong Hong, C E. Rasmussen, Tommy Chang, Michael O. Shneier

Abstract

In an outdoor, off-road mobile robotics environment, it is important to identify objects that can affect the vehicle''s ability to traverse its planned path, and to determine their three-dimensional characteristics. In this paper, a combination of three elements is used to accomplish this task. An imaging ladar collects range images of the scene. A color camera, whose position relative to the ladar is known, is used to gather color images. Information extracted from these sensors is used to build a world model, a representation of the current state of the world. The world model is used actively in the sensing to predict what should be visible in each of the sensors during the next imaging cycle. The paper explains how the combined use of these three types of information leads to a robust understanding of the local environment surrounding the robotic vehicle for two important tasks: puddle/pond avoidance and road sign detection. Applications of this approach to road detection are also discussed.
Citation
Fusing Ladar and Color Image Information for Mobile Robot Feature Detection and Tracking
Volume
7

Keywords

image registration, ladar sensing, puddle detection, road following, road sign detection, robot vehicle, sensor fusion, world model

Citation

, T. , Rasmussen, C. , Chang, T. and Shneier, M. (2002), Fusing Ladar and Color Image Information for Mobile Robot Feature Detection and Tracking, Fusing Ladar and Color Image Information for Mobile Robot Feature Detection and Tracking (Accessed May 19, 2024)

Issues

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Created March 1, 2002, Updated February 17, 2017