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Planning Complex Inspection Tasks Using Redundant Roadmaps

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Robotics Research

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 100))

Abstract

The aim of this work is fast, automated planning of robotic inspections involving complex 3D structures. A model comprised of discrete geometric primitives is provided as input, and a feasible robot inspection path is produced as output. Our algorithm is intended for tasks in which 2.5D algorithms, which divide an inspection into multiple 2D slices, and segmentation-based approaches, which divide a structure into simpler components, are unsuitable. This degree of 3D complexity has been introduced by the application of autonomous in-water ship hull inspection; protruding structures at the stern (propellers, shafts, and rudders) are positioned in close proximity to one another and to the hull, and clearance is an issue for a mobile robot. A global, sampling-based approach is adopted, in which all the structures are simultaneously considered in planning a path. First, the state space of the robot is discretized by constructing a roadmap of feasible states; construction ceases when each primitive is observed by a specified number of states. Once a roadmap is produced, the set cover problem and traveling salesman problem are approximated in sequence to build a feasible inspection tour. We analyze the performance of this procedure in solving one of the most complex inspection planning tasks to date, covering the stern of a large naval ship, using an a priori triangle mesh model obtained from real sonar data and comprised of 100,000 primitives. Our algorithm generates paths on a par with dual sampling, with reduced computational effort.

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Acknowledgments

We would like to thank Dr. J. Vaganay and K. Shurn of Bluefin Robotics for essential field testing support in gathering the ship hull datasets. This work was supported by the Office of Naval Research under Grant N00014-06-10043, monitored by Dr. T.F. Swean.

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Authors and Affiliations

  1. Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, UK

    Brendan Englot & Franz Hover

Authors
  1. Brendan Englot
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  2. Franz Hover
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Corresponding author

Correspondence to Brendan Englot .

Editor information

Editors and Affiliations

  1. Robotics and Intelligent Machines, Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Henrik I. Christensen

  2. Department of Computer Science, Stanford University, Stanford, California, USA

    Oussama Khatib

Appendix

Appendix

We give a table of open-source software resources used in our coverage path planning implementation (See Table 3).

Table 3 Resources used for coverage path planning software implementation
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Englot, B., Hover, F. (2017). Planning Complex Inspection Tasks Using Redundant Roadmaps. In: Christensen, H., Khatib, O. (eds) Robotics Research . Springer Tracts in Advanced Robotics, vol 100. Springer, Cham. https://doi.org/10.1007/978-3-319-29363-9_19

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  • DOI: https://doi.org/10.1007/978-3-319-29363-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29362-2

  • Online ISBN: 978-3-319-29363-9

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