Skip to main content
Log in

A Sensor Placement Algorithm for a Mobile Robot Inspection Planning

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

In this paper, we address the inspection planning problem to “see” the whole area of the given workspace by a mobile robot. The problem is decoupled into the sensor placement problem and the multi-goal path planning problem to visit found sensing locations. However the decoupled approach provides a feasible solution, its overall quality can be poor, because the sub-problems are solved independently. We propose a new randomized approach that considers the path planning problem during solution process of the sensor placement problem. The proposed algorithm is based on a guiding of the randomization process according to prior knowledge about the environment. The algorithm is compared with two algorithms already used in the inspection planning. Performance of the algorithms is evaluated in several real environments and for a set of visibility ranges. The proposed algorithm provides better solutions in both evaluated criterions: a number of sensing locations and a length of the inspection path.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Chin, W.-P., Ntafos, S.: Optimum watchman routes. In: SCG ’86: Proceedings of the Second Annual Symposium on Computational Geometry, pp. 24–33, Yorktown Heights, New York. ACM (1986)

  2. Packer, E.: Robust geometric computing and optimal visibility coverage. PhD thesis, Stony Brook University, New York (2008)

  3. Danner, T., Kavraki, L.E.: Randomized planning for short inspection paths. In: Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), pp. 971–976, San Francisco, CA. IEEE (2000)

  4. Culberson, J.C., Reckhow, R.A.: Covering polygons is hard. J. Algorithms 17(1), 2–44 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  5. Tan, X., Hirata, T.: Finding shortest safari routes in simple polygons. Inf. Process. Lett. 87(4), 179–186 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  6. Ntafos, S.C.: Watchman routes under limited visibility. Comput. Geom. 1, 149–170 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  7. Li, F., Klette, R.: An approximate algorithm for solving the watchman route problem. In: RobVis, pp. 189–206 (2008)

  8. Goodman, J.E., O’Rourke, J. (eds.): Handbook of Discrete and Computational Geometry. CRC Press, Boca Raton (2004)

    MATH  Google Scholar 

  9. González-Baños, H.H., Hsu, D., Latombe, J.-C.: Motion planning: recent developments. In: Ge, S.S., Lewis, F.L. (eds.) Autonomous Mobile Robots: Sensing, Control, Decision-Making and Applications, Chapter 10. CRC (2006)

  10. Wang, P.: View planning with combined view and travel cost. PhD thesis, Simon Fraser University (2007)

  11. González-Baños, H.H., Latombe, J.-C.: Planning robot motions for range-image acquisition and automatic 3d model construction. In: AAAI Fall Symposium (1998)

  12. Hörster, E., Lienhart, R.: On the optimal placement of multiple visual sensors. In: VSSN ’06: Proceedings of the 4th ACM International Workshop on Video Surveillance and Sensor Networks, pp. 111–120, New York, NY. ACM (2006)

  13. Erdem, U.M., Sclaroff, S.: Automated camera layout to satisfy task-specific and floor plan-specific coverage requirements. Comput. Vis. Image Underst. 103(3), 156–169 (2006)

    Article  Google Scholar 

  14. Osais, Y.E., St-Hilaire, M., Yu, F.R.: Directional sensor placement with optimal sensing range, field of view and orientation. Mob. Netw. Appl. 15(2), 216–225 (2008)

    Article  Google Scholar 

  15. Kazazakis, G.D., Argyros, A.A.: Fast positioning of limited visibility guards for the inspection of 2d workspaces. In: Proceedings of the IEEE/RSJ Int. Conference on Intelligent Robots and Systems (IROS2002), Lausanne (2002)

  16. Scott, W.R., Roth, G., Rivest, J.-F.: View planning for automated three-dimensional object reconstruction and inspection. ACM Comput. Surv. 35(1), 64–96 (2003)

    Article  Google Scholar 

  17. Blaer, P.S., Allen, P.K.: Data acquisition and view planning for 3-d modeling tasks. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2007), pp. 417–422, 29 October–2 November 2007

  18. Nüchter, A., Surmann, H., Hertzberg, J.: Planning robot motion for 3d digitalization of indoor environments. In: Proceedings of the 11th International Conference on Advanced Robotics (ICAR), pp. 222–227 (2003)

  19. González-Baños, H.H., Latombe, J.-C.: Navigation strategies for exploring indoor environments. Int. J. Rob. Res. 21(10–11), 829–848 (2002)

    Article  Google Scholar 

  20. González-Banos, H.H.: A randomized art-gallery algorithm for sensor placement. In: SCG ’01: Proceedings of the Seventeenth Annual Symposium on Computational Geometry, pp. 232–240. ACM, New York (2001)

    Chapter  Google Scholar 

  21. Lavalle, S.M.: Planning Algorithms. Cambridge University Press (2006)

  22. Overmars, M.H., Welzl, E.: New methods for computing visibility graphs. In: SCG ’88: Proceedings of the Fourth Annual Symposium on Computational Geometry, pp. 164–171. ACM, New York (1988)

    Chapter  Google Scholar 

  23. Seidel, R.: A simple and fast incremental randomized algorithm for computing trapezoidal decompositions and for triangulating polygons. Comput. Geom. Theory Appl. 1(1), 51–64 (1991)

    MathSciNet  MATH  Google Scholar 

  24. Latecki, L.J., Lakämper, R.: Convexity rule for shape decomposition based on discrete contour evolution. Comput. Vis. Image Underst. 73(3), 441–454 (1999)

    Article  Google Scholar 

  25. Wolter, D., Richter, K.-F.: Schematized aspect maps for robot guidance. In: Proceedings of the ECAI Workshop Cognitive Robotics (CogRob) (2004)

  26. Applegate, D., Bixby, R., Chvátal, V., Cook, W.: CONCORDE TSP Solver. http://www.tsp.gatech.edu/concorde.html (2003). Accessed 23 July 2010

  27. Applegate, D., Cook, W., Rohe, A.: Chained lin-kernighan for large traveling salesman problems. INFORMS J. Comput. 15(1), 82–92 (2003)

    Article  MathSciNet  Google Scholar 

  28. Chen, Z., Birchfield, S.T.: Qualitative vision-based path following. IEEE Transactions on Robotics 25(3), 749–754 (2009)

    Article  Google Scholar 

  29. Sohn, H.J., Kim, B.K.: Vecslam: an efficient vector-based slam algorithm for indoor environments. J. Intell. Robot. Syst. 56(3), 301–318 (2009)

    Article  MATH  Google Scholar 

  30. CGAL—Computational Geometry Algorithms Library. http://www.cgal.org (2004). Accessed 23 July 2010

  31. JTS Topology Suite. http://www.vividsolutions.com/jts/jtshome.htm. Version 1.5 (2004). Accessed 23 July 2010

  32. Diablo Caffe JDK 1.6.0-7. http://www.freebsdfoundation.org/downloads/java.shtml (2009). Accessed 23 July 2010

  33. Wein, R., van den Berg, J.P., Halperin, D.: The visibility–voronoi complex and its applications. In: SCG ’05: Proceedings of the Twenty-First Annual Symposium on Computational Geometry, pp. 63–72. ACM, New York (2005)

    Chapter  Google Scholar 

  34. Huang, W.H., Beevers, K.R.: Complete Topological Mapping with Sparse Sensing. Technical Report 6, Rensselaer Polytechnic Institute Department of Computer Science (2005)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jan Faigl.

Additional information

The work has been supported by the Ministry of Education of the Czech Republic under program “National research program II” by the project 2C06005.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Faigl, J., Kulich, M. & Přeučil, L. A Sensor Placement Algorithm for a Mobile Robot Inspection Planning. J Intell Robot Syst 62, 329–353 (2011). https://doi.org/10.1007/s10846-010-9449-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-010-9449-0

Keywords

Navigation