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Conference Papers Year : 2020

Photometric Path Planning for Vision-Based Navigation

Abstract

We present a vision-based navigation system that uses a visual memory to navigate. Such memory corresponds to a topological map of key images created from moving a virtual camera over a model of the real scene. The advantage of our approach is that it provides a useful insight into the navigability of a visual path without relying on a traditional learning stage. During the navigation stage, the robot is controlled by sequentially comparing the images stored in the memory with the images acquired by the onboard camera. The evaluation is conducted on a robotic arm equipped with a camera and the model of the environment corresponds to a top view image of an urban scene.
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Dates and versions

hal-02492459 , version 1 (16-03-2020)

Identifiers

  • HAL Id : hal-02492459 , version 1

Cite

Eder Rodriguez, Guillaume Caron, Claude Pegard, David Lara Alabazares. Photometric Path Planning for Vision-Based Navigation. IEEE International Conference on Robotics and Automation, May 2020, Paris, France. ⟨hal-02492459⟩
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