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A Method of Boundary Following by a Wheeled Mobile Robot Based on Sampled Range Information

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Abstract

In this paper, we propose a control law for navigating a robot along the boundary of an obstacle, using sampled line-of-sight obstacle distance data. By forming some assumptions about the shape of the obstacle, we generate constraints suitable for navigation using a model predictive control type approach. We show how a target point may be generated to facilitate the desired motion. The proposed method is suitable for vehicles with unicycle dynamics, and has the advantage of being able to vary the vehicles speed and following distance to adapt to the obstacle. We are able to show collision avoidance, complete transversal of the obstacle and finite completion time for transversing a finite boundary segment. Possible extensions to target convergence and moving obstacles are outlined. Simulations and experiments confirm the validity of the method.

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References

  1. Bemporad, A., Marco, M.D., Tesi, A.: Sonar–based wall–following control of mobile robots. J. Dyn. Syst. 122, 226–230 (2000)

    Article  Google Scholar 

  2. Brooks, A., Kaupp, T., Makarenko, A.: Randomised MPC–based motion–planning for mobile robot obstacle avoidance. In Proceedings of the 2009 IEEE International Conference on Robotics and Automation, pp. 397–402. Kobe, Japan (2009)

  3. Carelli, R., Freire, E.O.: Corridor navigation and wall–following stable control for sonar–based mobile robots. Robot. Auton. Syst. 45, 235–247 (2003)

    Article  Google Scholar 

  4. Durrant–Whyte, H., Bailey, T.: Simultaneous localization and mapping: part I. IEEE Robot. Autom. Mag. 13(2), 99–110 (2006)

    Article  Google Scholar 

  5. Fox, D., Burgard, W., Thrun, S.: The dynamic window approach to collision avoidance. IEEE Robot. Autom. Mag. 4(1), 23–33 (1997)

    Article  Google Scholar 

  6. Ge, S.S., Lai, X., Mamun, A.A.: Boundary following and globally convergent path planning using instant goals. IEEE Trans. Syst. Man Cybern., Part B, Cybern. 35(2), 240–254 (2005)

    Article  Google Scholar 

  7. Ge, S.S., Lai, X., Mamun, A.A.: Sensor–based path planning for nonholonomic mobile robots subject to dynamic constraints. Robot. Auton. Syst. 55(7), 513–526 (2007)

    Article  Google Scholar 

  8. Hoy, M., Matveev, A.S., Garratt, M., Savkin, A.V.: Collision free navigation of an autonomous unmanned helicopter in unknown urban environments: sliding mode and MPC approaches. Robotica 30(4), 537–550 (2012)

    Article  Google Scholar 

  9. Hoy, M., Matveev, A.S., Savkin, A.V.: Collision free cooperative navigation of multiple wheeled robots in unknown cluttered environments. Robot. Auton. Syst. 60(10), 1253–1266 (2012)

    Article  Google Scholar 

  10. Hoy, M., Savkin, A.V.: A method for border patrolling navigation of a mobile robot. In: Proceedings of the 9th IEEE International Conference on Control and Automation, pp. 130–135. Santiago, Chile (2011)

  11. Huang, L.: Wall–following control of an infrared sensors guided wheeled mobile robot. Int. J. Intell. Syst. 7(1), 106–117 (2009)

    Google Scholar 

  12. Jefferies, M.E., Yeap, W. (eds.): Robotics and Cognitive Approaches to Spatial Mapping, vol. 38. Springer, Berlin Heidelberg (2008)

    Google Scholar 

  13. Kim, J., Zhang, F., Egerstedt, M.: Curve tracking control for autonomous vehicles with rigidly mounted range sensors. J. Intell. Robot. Syst. 56(2), 177–197 (2009)

    Article  MATH  Google Scholar 

  14. Kuwata, Y., Richards, A., Schouwenaars, T., How, J.P.: Distributed robust receding horizon control for multivehicle guidance. IEEE Trans. Control Syst. Technol. 15(4), 627–641 (2007)

    Article  Google Scholar 

  15. Langer, R.A., Coelho, L.S., Oliveira, G.H.: K–bug–a new bug approach for mobile robot’s path planning. In: Proceedings of the IEEE International Conference on Control Applications, pp. 403–408. Singapore (2007)

  16. Low, E.M.P., Manchester, I.R., Savkin, A.V.: A biologically inspired method for vision-based docking of wheeled mobile robots. Robot. Auton. Syst. 55(10), 769–784 (2007)

    Article  Google Scholar 

  17. Lumelsky, V.J., Skewis, T.: Incorporating range sensing in the robot navigation function. IEEE Trans. Syst. Man Cybern. 20(5), 1058–1069 (1990)

    Article  Google Scholar 

  18. Matveev, A.S., Hoy, M., Savkin, A.V.: The problem of boundary following by a unicycle–like robot with rigidly mounted sensors [online]. Robot. Auton. Syst. 61(3), 312–327 (2013)

    Article  Google Scholar 

  19. Matveev, A.S., Hoy, M.C., Savkin, A.V.: A method for reactive navigation of nonholonomic robots in the presence of obstacles. In: Proceedings of the IFAC World Congress (2011)

  20. Matveev, A.S., Teimoori, H., Savkin, A.V.: A method for guidance and control of an autonomous vehicle in problems of border patrolling and obstacle avoidance. Automatica 47(3), 515–514 (2011)

    Article  MathSciNet  Google Scholar 

  21. Matveev, A.S., Teimoori, H., Savkin, A.V.: Navigation of a unicycle–like mobile robot for environmental extremum seeking. Automatica 47(1), 85–91 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  22. Matveev, A.S., Wang, C., Savkin, A.V.: Real–time navigation of mobile robots in problems of border patrolling and avoiding collisions with moving and deforming obstacles. Robot. Auton. Syst. 60(6), 769–788 (2012)

    Article  Google Scholar 

  23. Minguez, J., Montano, L.: Nearness diagram (ND) navigation: collision avoidance in troublesome scenarios. IEEE Trans. Robot. Autom. 20(1), 45–59 (2004)

    Article  Google Scholar 

  24. Moghadam, P., Wijesoma, W.S., Dong, J.F.: Improving path planning and mapping based on stereo vision and lidar. In: Proceedings of the International Conference on Control, Automation, Robotics and Vision. Hanoi, Vietnam (2008)

  25. Negishi, Y., Miura, J., Shirai, Y.: Mobile robot navigation in unknown environments using omnidirectional stereo and laser range finder. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 3, pp. 2737–2742. Sendai, Japan (2004)

  26. Ng, J., Braunl, T.: Performance comparison of bug navigation algorithms. J. Intell. Robot. Syst. 50(1), 73–84 (2007)

    Article  Google Scholar 

  27. Ogren, P., Leonard, N.E.: A convergent dynamic window approach to obstacle avoidance. IEEE Trans. Robot. 21(2), 188–195 (2005)

    Article  Google Scholar 

  28. Richards, A., How, J.P.: Robust variable horizon model predictive control for vehicle maneuvering. Int. J. Robust Nonlinear Control 16(7), 333–351 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  29. Sanz-Cortiella, R., Llorens-Calveras, J., Rosell-Polo, J.R., Gregorio-Lopez, E., Palacin-Roca, J.: Characterisation of the LMS200 laser beam under the influence of blockage surfaces. Influence on 3D scanning of tree orchards. Sensors 11(3), 2751–2772 (2011)

    Article  Google Scholar 

  30. Shkel, A.M., Lumelsky, V.J.: Incorporating body dynamics into sensor–based motion planning: the maximum turn strategy. IEEE Trans. Robot. Autom. 13(6), 873–880 (1997)

    Article  Google Scholar 

  31. Teimoori, H., Savkin, A.V.: A biologically inspired method for robot navigation in a cluttered environment. Robotica 28(5), 637–648 (2010)

    Article  Google Scholar 

  32. Teimoori, H., Savkin, A.V.: Equiangular navigation and guidance of a wheeled mobile robot based on range–only measurements. Robot. Auton. Syst. 58(2), 203–215 (2010)

    Article  Google Scholar 

  33. Thrun, S.: Learning occupancy grid maps with forward sensor models. Auton. Robots 15(2), 111–127 (2003)

    Article  Google Scholar 

  34. Toibero, J.M., Roberti, F., Carelli, R.: Stable contour–following control of wheeled mobile robots. Robotica 27(1), 1–12 (2009)

    Article  Google Scholar 

  35. Travis, W., Simmons, A.T., Bevly, D.M.: Corridor navigation with a LiDAR/INS kalman filter solution. In: Proceedings of the IEEE Intelligent Vehicles Symposium. Tokyo, Japan (2005)

  36. Ulrich, I., Borenstein, J.: VFH+: reliable obstacle avoidance for fast mobile robots. In: Proceedings of the IEEE International Conference on Robotics and Automation, vol. 2, pp. 1572–1577. Leuven, Belgium (1998)

  37. Ulrich, I., Borenstein, J.: VFH*: local obstacle avoidance with look–ahead verification. In: Proceedings of the IEEE International Conference on Robotics and Automation, vol. 3, pp. 2505–2511. San Francisco, CA, USA (2000)

  38. Yata, T., Kleeman, L., Yuta, S.: Wall following using angle information measured by a single ultrasonic transducer. In: Proceedings of the IEEE International Conference on Robotics and Automation, vol. 2, pp. 1590–1596. Leuven, Belgium (1998)

  39. Zhang, Z.: Iterative point matching for registration of free–form curves and surfaces. Int. J. Comput. Vis. 13(2), 119–152 (1994)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, Australia

    Michael Hoy

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  1. Michael Hoy
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Correspondence to Michael Hoy.

Additional information

This work was partially supported by the Australian Research Council.

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Hoy, M. A Method of Boundary Following by a Wheeled Mobile Robot Based on Sampled Range Information. J Intell Robot Syst 72, 463–482 (2013). https://doi.org/10.1007/s10846-013-9825-7

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  • DOI: https://doi.org/10.1007/s10846-013-9825-7

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