A Survey on Randomized Sampling-Based Path Optimization Methods

Article Preview

Abstract:

Randomized sampling-based motion planners could efficiently generate collision-free motion paths. However, these paths have some quality problems (with respect to quality measures, such as path length, clearance and smoothness), especially in high dimensional configuration spaces. Thus, researchers studied some path optimization methods to improve path quality and to make paths suitable for practical applications. This paper reviews some of the most influential path optimization methods and gives an overall perspective on the most widely used ideas in the field.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

652-660

Citation:

Online since:

December 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] T. Berglund, U. Erikson, H. Jonsson, K. Mrozek, and I. Soderkvist: Int. Conf. on Computational Intelligence for Modeling Control and Automation (2001).

Google Scholar

[2] F. Lamireaux, D. Bonnafous, and C. V. Geem: Workshop Control Problems in Robotics and Automation (2002), pp.1-18.

Google Scholar

[3] F. Lamiraux and J. -P. Laumond: Smooth motion planning for car-like vehicles (IEEE Trans. on Robotics and Automation, 2001).

DOI: 10.1109/70.954762

Google Scholar

[4] M. Yamamoto, M. Iwamura, and A. Mohri: IEEE Int. Conf. on Robotics and Automation (1999), pp.2958-2963.

Google Scholar

[5] G. Song and N. M. Amato: IEEE Int. Conf. on Intelligent Robots and Systems (2001), pp.37-42.

Google Scholar

[6] B. Baginski: Int. Workshop on Robotics in the Alpe-Adria-Danube Region (1997), pp.247-252.

Google Scholar

[7] B. Baginski: Motion planning for manipulators with many degrees of freedom - the BB-method (Ph.D. dissertation, Technische Universität Münchena 1998).

Google Scholar

[8] R. Bohlin: Motion planning for industrial robots (Ph.D. dissertation, Goteborg Univ., Sweden 1999).

Google Scholar

[9] D. Hsu, J. -C. Latombe, and S. Sorkin: IEEE Int. Symp. on Assembly and Task (1999), pp.280-285.

Google Scholar

[10] C. V. Geem, T. SimCon, and J. -P. Laumond: IEEE Int. Conf. on Robotics and Automation (1999), pp.1770-1775.

Google Scholar

[11] D. Nieuwenhuisen and M. H. Overmars: Motion planning for camera movements (Utrecht Univ., Technical Report 2003-004, 2003).

Google Scholar

[12] G. Song and N. Amato: Using motion planning to study protein folding pathways (Journal of Computational Biology).

Google Scholar

[13] J. J. Kuffner, K. Nishiwaki, S. Kagami, M. Inaba, and H. Inoue: IEEE Int. Conf. on Robotics and Automation (2001), pp.692-698.

Google Scholar

[14] H. Choset, K. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. Kavraki, and S. Thrun, in Principles of robot motion: Theory, algorithms, and implementations, 1st ed,. Cambridge, MA: MIT Press, (2005).

DOI: 10.1017/s0269888907218016

Google Scholar

[15] J. -C. Latombe, in Robot motion planning. Boston, MA: Kluwer Academic Publishers, (1991).

Google Scholar

[16] S. M. LaValle, in Planning Algorithms. Cambridge, U.K.: Cambridge Univ. Press, (2006).

Google Scholar

[17] S. R. Lindemann and S. M. LaValle: Proc. 11th Int. Symp. of Robotics Research (2003).

Google Scholar

[18] J. Canny and J. Reif: IEEE Symp. on Foundations of Computer Science (1987), pp.49-60.

Google Scholar

[19] T. Asano, D. Kirkpatrick, and C. Yap: Proc. 12th ACM Symp. on Compution Geometry (1996), pp.252-263.

Google Scholar

[20] J. Reif and H. Wang: IEEE Workshop on Foundations of Robotics (1998), pp.49-57.

Google Scholar

[21] J. S. B. Mitchell, in Handbook of Discrete and Computational Geometry. Boca Raton, FL: CRC, (2004).

Google Scholar

[22] V. Boor, A. Kamphuis, C. Gem, E. Schmitzberger, and J. Bouchet: Formalisation of path quality (Delivery MOLOG Project, 2000).

Google Scholar

[23] L. Kavraki and J. -C. Latombe: IEEE Int. Conf. on Robotics and Automation (1994), pp.2138-2139.

Google Scholar

[24] L. Kavraki, P. Svestka, J. -C. Latombe, and M. H. Overmars: Probabilistic roadmaps for path planning in high-dimensional configuration spaces (IEEE Trans. on Robotics and Automation, 1996).

DOI: 10.1109/70.508439

Google Scholar

[25] S. M. LaValle: Rapidly-exploring random trees: A new tool for path planning (Iowa State Univ., Technical Report TR98-11, 1998).

Google Scholar

[26] J. J. Kuffner and S. M. LaValle: IEEE Int. Conf. on Robotics and Automation (2000), pp.995-1001.

Google Scholar

[27] E. W. Dijkstra: A note on two problems in connexion with graphs (Numerische Mathematik, 1959).

Google Scholar

[28] J. Orlin: Network Flows (New Jersey: Prentice Hall, Upper Saddle River, 1993).

Google Scholar

[29] A. Papadatos: Research on motion planning of autonomous mobile robot (M.S. thesis, Naval Postgraduate School, Monterrey, California, USA, 1996).

Google Scholar

[30] J. Kim, R. A. Pearce, and N. M. Amato: IEEE Int. Conf. on Robotics and Automation (2003), pp.2424-2429.

Google Scholar

[31] R. Geraerts and M. H. Overmars: Workshop on the Algorithmic Founda- tions of Robotics (2002), pp.43-57.

Google Scholar

[32] C. Nissoux, T. Simeon, and J. -P. Laumond: IEEE Int. Conf. on Intelligent Robots and Systems (1999), pp.1316-1321.

Google Scholar

[33] R. Geraerts and M. H. Overmars: Conf. on Intelligent Autonomous Systems (2004), pp.600-609.

Google Scholar

[34] R. Geraerts and M. H. Overmars: IEEE Int. Conf. on Methods and Models in Automation and Robotics (2005), pp.531-536.

Google Scholar

[35] D. Nieuwenhuisen and M. H. Overmars: IEEE Int. Conf. on Robotics and Automation (2004), pp.446-452.

Google Scholar

[36] R. Geraens and M. H. Overmars: IEEE Int. Conf. on Robotics and Automation (2004), pp.2386-2392.

Google Scholar

[37] R. Geraerts and M. H. Overmars: Creating high-quality paths for motion planning (Int. Journal of Robotics Research, 2007).

Google Scholar

[38] L. E. Kavrak and J. -C. Latombe, in Probabilistic roadmaps for robot path planning, Practical Motion Planning in Robotics: Current Approaches and Future Directions, edtied by K. Gupta and A. del Pobil, John Wiley, (1998).

Google Scholar

[39] P. Isto: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (2002), pp.2323-2328.

Google Scholar

[40] J. de Smith: Distance and path: the development, interpretation and application of distance measurement in mapping and modeling (Ph.D. dissertation, Univ. College, Univ. of London, London, U.K., 2003).

Google Scholar

[41] L. Feng and Q. Jia: Improved algorithm of RRT path planning based on comparison optimization , (Computer Engineering and Applications, 2011).

Google Scholar

[42] S. A. Wilmarth, N. M. Amato, and P. F. Stiller: IEEE Int. Conf. on Robotics and Automation (1999), pp.1024-1031.

Google Scholar

[43] E. Aurenhammer: Voronoi diagrams: A survey of a fundamental geometric data structure (ACM Computer Surver, 1991).

DOI: 10.1145/116873.116880

Google Scholar

[44] S. A. Wilmarth, N. M. Amato, and P. F. Stiller: Proc. ACM Symp. on Computational Geometry (1999), pp.173-180.

Google Scholar

[45] J. -M. Lien, S. L. Thomas, and N. M. Amato: IEEE Int. Conf. on Robotics and Automation (2003), pp.4439-4444.

Google Scholar

[46] R. Geraerts and M. H. Overmars: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (2005), pp.679-684.

Google Scholar

[47] E. Schmitzberger, J. L. Bouchet, M. Dufaut, D. Wolf, and R. Husson: IEEE/RSJ Int. Conf. on lntelligent Robots and Systems (2002), pp.2317-2322.

DOI: 10.1109/irds.2002.1041613

Google Scholar

[48] G. Song, S. Miller, and N. M. Amato: IEEE Int. Conf. on Robotics and Automation (2001), pp.1500-1505.

Google Scholar

[49] D. Nieuwenhuisen, A. Kamphuis, M. Mooijekind, and M. H. Overmars: Automatic construction of high quality roadmaps for path planning (Utrecht Univ., Technical Report UU-CS-2004-068, 2004).

Google Scholar

[50] R. Wein, J. van den Berg, and D. Halperin: The visibility-voronoi complex and its applications (Computational Geometry: Theory and Applications, 2007).

DOI: 10.1016/j.comgeo.2005.11.007

Google Scholar

[51] R. Geraerts and M. H. Overmars: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (2006), pp.4355-4361.

Google Scholar

[52] S. Karaman and E. Frazzoli: submitted to Int. Journal of Robotic Research.

Google Scholar

[53] D. Ferguson and A. Stentz: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (2006), pp.5369-5385.

Google Scholar

[54] B. Raveh, A. Enosh, and D. Halperin: A little more, a lot better: Improving path quality by a path-merging algorithm (IEEE Trans. on Robotics, 2011).

DOI: 10.1109/tro.2010.2098622

Google Scholar

[55] A. Kamphuis and M. H. Overmars: Eurographics/ACM SIGGRAPH Symp. on Computer Animation (2004), pp.19-28.

Google Scholar

[56] R. Wein, J. Berg, and D. Halperin: Int. Workshop on the Algorithmic Foundations of Robotics (2006).

Google Scholar

[57] J. Pettre, P. de H. Ciechomski, J. Maim, B. Yersin, J. -P. Laumond, and D. Thalmann: Real-time navigating crowds: Scalable simulation and rendering (Computer Animation and Virtual Worlds, 2006).

DOI: 10.1002/cav.147

Google Scholar

[58] R. Geraerts and M. H. Overmars: The corridor map method: A general framework for real-time high-quality path planning (Computer Animation and Virtual Worlds, 2007).

DOI: 10.1002/cav.166

Google Scholar

[59] R. Geraerts: IEEE Int. Conf. on Robotics and Automation (2010), p.1997-(2004).

Google Scholar

[60] I. Karamouzas, R. Geraerts, and M. H. Overmars: The 4th Int. Conf. on the Foundations of Digital Games (2009), p.113–120.

Google Scholar