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Outdoor Mapping and Navigation Using Stereo Vision

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Part of the Springer Tracts in Advanced Robotics book series (STAR,volume 39)

Introduction

We consider the problem of autonomous navigation in an unstructured outdoor environment. The goal is for a small outdoor robot to come into a new area, learn about and map its environment, and move to a given goal at modest speeds (1 m/s). This problem is especially difficult in outdoor, off-road environments, where tall grass, shadows, deadfall, and other obstacles predominate. Not surprisingly, the biggest challenge is acquiring and using a reliable map of the new area. Although work in outdoor navigation has preferentially used laser rangefinders [14,2,6], we use stereo vision as the main sensor. Vision sensors allow us to use more distant objects as landmarks for navigation, and to learn and use color and texture models of the environment, in looking further ahead than is possible with range sensors alone.

Keywords

  • Ground Plane
  • Stereo Vision
  • Obstacle Detection
  • Global Planning
  • Visual Odometry

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Konolige, K., Agrawal, M., Bolles, R.C., Cowan, C., Fischler, M., Gerkey, B. (2008). Outdoor Mapping and Navigation Using Stereo Vision. In: Khatib, O., Kumar, V., Rus, D. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77457-0_17

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  • DOI: https://doi.org/10.1007/978-3-540-77457-0_17

  • Publisher Name: Springer, Berlin, Heidelberg

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