MOBILE ROBOT - A Complete Framework for 2D-path Planning and Motion Planning

Giuseppe Zuffanti, Costantino Scozzafava

2011

Abstract

In this work we focus on the problem of 2D path planning and motion planning for a mobile robot. The goodness of a path planning and motion planning methods can be evaluated primarily through the parameters such as safety of generated trajectory speeds and robustness against dynamic changes of the environment. In all applications that use mobile robots, the motion planning problem is of crucial importance. According to different applications one can put emphasis on the previous characteristics listed, potentially to the detriment of the others. Typically, methods that generate high trajectory speeds for the navigating robot appears to be less robust and safe. The importance that the path planning and the motion planning problem play in practical applications is also demonstrated by the several techniques developed to tackle them. We propose a complete framework which creates a clear shortest path for a robot in an environment with static obstacles and generates, in real time, the accurate trajectory taking into account the presence of dynamics obstacles. Application of the framework to the case of a differential drive robot in a dynamic indoor environment is shown and the proposed approach has been tested both with simulation and real data.

References

  1. Aicardi, M., Casalino, G., Balestrino, A., and Bicchi, A. (1994). Closed loop smooth steering of unicycle-like vehicles. In Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on, volume 3, pages 2455 -2458.
  2. Alami, R., Chatila, R., Fleury, S., Ghallab, M., and Ingrand, F. (1998). An architecture for autonomy. International Journal of Robotics Research, 17:315-337.
  3. Albagul, A. and Wahyudi (2004). Dynamic modeling and adaptive traction control for mobile robots. In Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE, volume 1, pages 614 - 620.
  4. Budanov, V. M. and Devyanin, Y. A. (2003). The motion of wheeled robots. Journal of Applied Mathematics and Mechanics, 67(2):215 - 225.
  5. Canny, J. F. (1988). The Complexity of Robot Motion Planning. MIT Press, Cambridge, MA.
  6. Chitsaz, H., LaValle, S. M., Balkcom, D. J., and Mason, M. T. (2006). Minimum wheel-rotation paths for differential-drive mobile robots. In Proceedings IEEE International Conference on Robotics and Automation.
  7. Delaunay, B. N. (1934). Sur la sphre vide. Bulletin of Academy of Sciences of the USSR, 6:793800.
  8. Geraerts, R. and Overmars, M. H. (2007). The corridor map method: Realtime high-quality path-planning. In Proceeding IEEE International Conference on Robotics and Automation, page 10231028.
  9. Latombe, J. C. (1991). Robot Motion Planning. Kluwer, Boston, MA.
  10. LaValle, S. M. (2006). Planning Algorithms. Cambridge University Press, Cambridge, UK, 1st edition.
  11. LaValle, S. M. and Kuffner, J. J. (1999). Randomized kinodynamic planning. In Proceedings IEEE International Conference on Robotics and Automation, page 73479.
  12. Liang, T. C. and Liu, J.-S. (2004). A bounded-curvature shortest path generation method for car-like mobile robot using cubic spiral. In Proceedings IEEE/RSJ In- ternational Conference on Intelligent Robots and Sys- tems, page 28192824.
  13. Lien, J.-M., Thomas, S. L., and Amato, N. M. (2003). A general framework for sampling on the medial axis of the free space. In Proceedings IEEE International Conference on Robotics and Automation, page 44394444.
  14. Masehian, E. and Movafaghpour, M. A. (2009). An adaptive sequential clustering algorithm for generating poly-line maps from range data scan in mobile robot explorationby. In International Conference on Automation Technology.
  15. Rimon, E. and Koditschek, D. E. (1992). Exact Robot Navigation Using Artificial Potential Fields. IEEE Trans. Robot. & Autom., 8(5):501-518.
  16. Siciliano, B., Sciavicco, L., Villani, L., and Oriolo, G. (2008). Robotics: Modelling, Planning and Control. Springer Publishing Company, Incorporated.
  17. Veeck, M. and Burgard, W. (2004). Learning polyline maps from range scan data acquired with mobile robots. In International Conference on Intelligent Robots and Systems.
Download


Paper Citation


in Harvard Style

Zuffanti G. and Scozzafava C. (2011). MOBILE ROBOT - A Complete Framework for 2D-path Planning and Motion Planning . In Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: MORAS, (ICINCO 2011) ISBN 978-989-8425-75-1, pages 417-426. DOI: 10.5220/0003648504170426


in Bibtex Style

@conference{moras11,
author={Giuseppe Zuffanti and Costantino Scozzafava},
title={MOBILE ROBOT - A Complete Framework for 2D-path Planning and Motion Planning},
booktitle={Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: MORAS, (ICINCO 2011)},
year={2011},
pages={417-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003648504170426},
isbn={978-989-8425-75-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: MORAS, (ICINCO 2011)
TI - MOBILE ROBOT - A Complete Framework for 2D-path Planning and Motion Planning
SN - 978-989-8425-75-1
AU - Zuffanti G.
AU - Scozzafava C.
PY - 2011
SP - 417
EP - 426
DO - 10.5220/0003648504170426