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Performance Comparison of Bug Navigation Algorithms

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Abstract

The Bug algorithm family are well-known robot navigation algorithms with proven termination conditions for unknown environments. Eleven variations of Bug algorithm have been implemented and compared against each other on the EyeSim simulation platform. This paper discusses their relative performance for a number of different environment types as well as practical implementation issues.

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References

  1. Lumelsky, V.J., Stepanov, A.A.: Dynamic path planning for a mobile automaton with limited information on the environment. IEEE Trans. Automat. Contr. 31, 1058–1063 (1986)

    Article  MATH  Google Scholar 

  2. Sankaranarayanan, A., Vidyasagar, M.: A new path planning algorithm for moving a point object amidst unknown obstacles in a plane. Proc. of the IEEE Int. Conf. Robot. Autom. 3, 1930–1936 (1990)

    Article  Google Scholar 

  3. Sankaranarayanan, A., Vidyasagar, M.: Path planning for moving a point object amidst unknown obstacles in a plane: a new algorithm and a general theory for algorithm development. Proc. of the IEEE Int. Conf. on Decision and Control 2, 1111–1119 (1990)

    Google Scholar 

  4. Kamon, I., Rivlin, E.: Sensory-based motion planning with global proofs. IEEE Trans. Robot. Autom. 13, 814–822 (1997)

    Article  Google Scholar 

  5. Noborio, H.: A path-planning algorithm for generation of an intuitively reasonable path in an uncertain 2-D workspace. Proc. of the Japan–USA Symposium on Flex. Autom. 2, 477–480, (1990)

    Google Scholar 

  6. Noborio, H., Maeda, Y., Urakawa, K.: A comparative study of sensor-based path-planning algorithms in an unknown maze. In Proc. of the IEEE/RSI Int. Conf. on Intelligent Robots and Systems 2, 909–916 (2000)

  7. Ng, J., Bräunl, T.: An analysis of bug algorithm termination. (2007, to appear)

  8. Kamon, I., Rivlin, E., Rimon, E.: TangentBug: a range-sensor based navigation algorithm. J. Robot. Res. 17(9), 934–953 (1998)

    Article  Google Scholar 

  9. Lumelsky, V.J., Skewis, T.: Incorporating range sensing in the robot navigation function. IEEE Trans. Syst. Man Cybern. 20, 1058–1068 (1990)

    Article  Google Scholar 

  10. Noborio, H., Urakawa, K.: Three or more dimensional sensor-based path planning algorithm HD-I. Proc. of the IEEE/RSI Int. Conf. on Intelligent Robots and Systems 3, 1699–1706 (1999)

    Google Scholar 

  11. Noborio, H., Nogami, R., Hirao, S.: A new sensor-based path-planning algorithm whose path length is shorter on the average. Proc. of the 2004 Int. Conf. Robot. Autom. 3, 2832–2839 (2004)

    Article  Google Scholar 

  12. Laubach, S.L., Burdick, J.W.: An autonomous sensor-based path-planner for planetary microrovers. Proc. of the IEEE Int. Conf. on Robot. Autom. 1, 347–354 (1999)

    Google Scholar 

  13. Magid, E., Rivlin, E.: CautiousBug: a competitive algorithm for sensor-based robot navigation. Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems 3, 2757–2762 (2004)

    Google Scholar 

  14. Bräunl, T.: Embedded Robotics, 2nd edn. Springer, Berlin Heidelberg New York (2006)

    MATH  Google Scholar 

  15. Latombe, J.C.: Robot Motion Planning. Kluwer, Dordrecht (1991)

    Google Scholar 

  16. Choset, H., Lynch, K., Hutchinson, K., Kantor, G., Burgard, W., Kavarki, L. and Thrun, S.: Principles of Robot Motion: Theory, Algorithms and Implementations. MIT, Cambridge, MA (2005)

    MATH  Google Scholar 

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Correspondence to Thomas Bräunl.

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Ng, J., Bräunl, T. Performance Comparison of Bug Navigation Algorithms. J Intell Robot Syst 50, 73–84 (2007). https://doi.org/10.1007/s10846-007-9157-6

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  • DOI: https://doi.org/10.1007/s10846-007-9157-6

Keywords

Navigation