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2017 | OriginalPaper | Chapter

2. Angle-Based Navigation Using the 1D Trifocal Tensor

Authors : Miguel Aranda, Gonzalo López-Nicolás, Carlos Sagüés

Published in: Control of Multiple Robots Using Vision Sensors

Publisher: Springer International Publishing

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Abstract

The first problem addressed in the monograph is how to enable mobile robots to autonomously navigate toward specific positions in an environment. Vision sensors have often been used for this purpose, supporting a behavior known as visual homing, in which the robot’s target location is defined by an image. This chapter describes a novel visual homing methodology for robots moving in a planar environment. The employed visual information consists of a set of omnidirectional images acquired previously at different locations (including the goal position) in the environment and the current image taken by the robot. One of the contributions presented is an algorithm that calculates the relative angles between all these locations, using the computation of the 1D trifocal tensor between views and an indirect angle estimation procedure. The tensor is particularly well suited for planar motion scenarios and provides important robustness properties to the presented technique. A further contribution within the proposed methodology is a novel control law that uses the available angles, with no range information involved, to drive the robot to the goal. This way, the method takes advantage of the strengths of omnidirectional vision, which provides a wide field of view and very precise angular information. The chapter includes a formal proof of the stability of the proposed control law, and the performance of the visual navigation method is illustrated through simulations and different sets of experiments with real images captured by cameras on board robotic mobile platforms.

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Metadata
Title
Angle-Based Navigation Using the 1D Trifocal Tensor
Authors
Miguel Aranda
Gonzalo López-Nicolás
Carlos Sagüés
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-57828-6_2