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Employing Observation Angles in Pose Recognition; Application for Teach-and-Repeat Robot Navigation

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9055))

Abstract

In this paper, a method is presented which uses landmark bearings to support navigation. The herein introduced approach expands on previous method that uses robust image features in conjunction with dead-reckoning to correct robot bearing. In the presented approach, a combination of omnidirectional camera, and exploiting the observation angles are used to address adjustment of positioning errors of the robot on the fly, without a need for dead-reckoning. This keeps the positioning deviation within specific bounds and thus avoids accumulative nature of dead-reckoning error.

Although this information is insufficient for absolute triangulation, under certain constraints it proves satisfactory for direction estimation. Detecting the arrival at the previously learned location or comparing relative distance of the landmarks for each observation point is also possible.

The presented approach was verified in simulation and on the real robot. Obtained results indicate the feasibility of the approach.

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References

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Correspondence to Martin Dörfler .

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Dörfler, M., Přeučil, L. (2015). Employing Observation Angles in Pose Recognition; Application for Teach-and-Repeat Robot Navigation. In: Hodicky, J. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2015. Lecture Notes in Computer Science(), vol 9055. Springer, Cham. https://doi.org/10.1007/978-3-319-22383-4_12

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  • DOI: https://doi.org/10.1007/978-3-319-22383-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22382-7

  • Online ISBN: 978-3-319-22383-4

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