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SIAR: A Ground Robot Solution for Semi-autonomous Inspection of Visitable Sewers

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Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 132))

Abstract

The SIAR platform is a six-wheeled ground robot with differential kinematic configuration and automatic width adjustment developed for the ECHORD++ Challenge on Urban Robotics: “Robots For The Inspection And The Clearance Of The Sewer Network In Cities”. This challenge proposes the development of a wireless robotic platform for long range inspection of large city sewers, which are currently not addressed by commercial solutions. SIAR leverages RGBD data for affordable and high-resolution 3D perception of its surroundings. This information is internally used for robot localization and safe navigation. Moreover, this information is also employed in high-level functionalities such as automatic defect inspection, the detection of serviceability losses and the generation of global 3D reconstructions of the environment. This chapter describes the main software and hardware architecture of the system. It also details the advances made over state-of-the-art techniques in order to take into account the particularities of this environment, i.e., localization in a GPS-denied area, navigation or communications, to name a few. Finally, the chapter presents experimental results on real sewers of Barcelona to demonstrate the reliability and suitability of the proposed solution.

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Notes

  1. 1.

    From Orbbec https://orbbec3d.com.

  2. 2.

    http://www.microhardcorp.com/nVIP2400.php.

  3. 3.

    All the code is open-source and can be found in https://github.com/robotics-upo/siar_packages.

References

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Correspondence to Fernando Caballero .

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Alejo, D., Mier, G., Marques, C., Caballero, F., Merino, L., Alvito, P. (2020). SIAR: A Ground Robot Solution for Semi-autonomous Inspection of Visitable Sewers. In: Grau, A., Morel, Y., Puig-Pey, A., Cecchi, F. (eds) Advances in Robotics Research: From Lab to Market. Springer Tracts in Advanced Robotics, vol 132. Springer, Cham. https://doi.org/10.1007/978-3-030-22327-4_13

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