Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
J.M. Ahuactzin and K. Gupta. The kinematic roadmap: A motion planning based global approach for inverse kinematics of redundant robots. IEEE Transactions on Robotics and Automation, 15(4):653–669, August 1999.
J.M. Ahuactzin, K. Gupta, and E. Mazer. Manipulation planning for redundant robots: A practical approach. International Journal of Robotics Research, 17(7):731–747, July 1998.
J.M. Ahuactzin, E. Mazer, and P. Bessiere. Fondements mathematiques d’algorithme “Fil d’Ariane”. Revue d’Intelligence Artificielle, 9(1):7–34, 1995.
J.M Ahuactzin, E.-G. Talbi, P. Bessiere, and E. Mazer. Using genetic algorithms for robot motion planning. In European Conference on Artificial Intelligence, pp. 671–5, 1992.
N.M. Amato, O.B. Bayazit, L.K. Dale, C. Jones, and D. Vallejo. OBPRM: An obstacle-based PRM for 3D workspaces. In Proceedings of Workshop on Algorithmic Foundations of Robotics, pp. 155–168, 1998.
N.M. Amato, O.B. Bayazit, L.K. Dale, C. Jones, and D. Vallejo. Choosing good distance metrics and local planners for probabilistic roadmap methods. IEEE Transactions on Robotics and Automation, 16(4):442–447, August 2000.
N.M. Amato and Y. Wu. A randomized roadmap method for path and manipulation planning. In Proceedings of IEEE Conference on Robotics and Automation, volume 1, pp. 113–120, 1996.
J. Barraquand and J.-C. Latombe. Robot motion planning: A distributed representation approach. International Journal of Robotics Research, 10(6):628–649, December 1991.
P. Bessiere, J.M. Ahuactzin, E.-G. Talbi, and E. Mazer. The “Ariadne’s clew” algorithm: Global planning with local methods. In Proceedings of Workshop on Algorithmic Foundations of Robotics, pp. 39–47, 1994.
R. Bohlin and L.E. Kavraki. Path planning using lazy PRM. In Proceedings of IEEE Conference on Robotics and Automation, pp. 521–528, 2000.
V. Boor, N. H. Overmars, and A. F. van der Stappen. The Gaussian sampling strategy for probabilistic roadmap planners. In Proceedings of IEEE Conference on Robotics and Automation, pp. 1018–1023, 1999.
M. S. Branicky, S. M. LaValle, K. Olson, and L. Yang. Quasi-randomized path planning. In Proc. IEEE Int’l Conf. on Robotics and Automation, pp. 1481–1487, 2001.
R. Brooks and T. Lozano-Pérez. A subdivision algorithm in configuration space for findpath with rotation. In International Joint Conference on Artificial Intelligence, pp. 799–806, 1983.
J. F. Canny. The Complexity of Robot Motion Planning. MIT Press, Cambridge, MA, 1988.
R. Geraerts and M. H. Overmars. A comparative study of probabilistic roadmap planners. In Proceedings of Workshop on Algorithmic Foundations of Robotics, pp. 43–57, 2002.
L.J. Guibas, C. Holleman, and L.E. Kavraki. A probabilistic roadmap planner for flexible objects with a workspace medial-axis-based sampling approach. In Proceedings of IEEE/RSJ Conference on Intelligent Robots and Systems, pp. 254–259, 1999.
L. Han and N.M. Amato. A kinematics-based probabilistic roadmap method for closed chain systems. In Proceedings of Workshop on Algorithmic Foundations of Robotics, 2000.
C. Holleman and L.E. Kavraki. A framework for using the workspace medial axis in PRM planners. In Proceedings of IEEE Conference on Robotics and Automation, pp. 1408–1413, 2000.
T. Horsch, F. Schwarz, and H. Tolle. Motion planning with many degrees of freedom — random reflections at c-space obstacles. In Proceedings of IEEE Conference on Robotics and Automation, pp. 3318–3323, 1994.
D. Hsu, L.E. Kavraki, J.-C. Latombe, and R. Motwani. Capturing the connectivity of high-dimensional geometric spaces by parallelizable random sampling techniques. In P. M. Pardalos and S. Rajasekaran, editors, Advances in Randomized Parallel Computing, pp. 159–182. Kluwer Academic Publishers, 1999.
D. Hsu, J.-C. Latombe, and R. Motwani. Path planning in expansive configuration spaces. International Journal of Computational Geometry and Applications, 9(4 & 5):495–512, 1999.
Y.K. Hwang and N. Ahuja. Path planning using a potential field representation. Technical Report UILU-ENG-8-2251, University of Illinois, October 1988.
S. Kambhampati and L.S. Davis. Multiresolution path planning for mobile robots. IEEE Journal of Robotics and Automation, 2(3):135–145, September 1986.
L.E. Kavraki. Random Networks in Configuration Space for Fast Path Planning. PhD thesis, Stanford University, Stanford, CA, 1994.
L.E. Kavraki, M. N. Kolountzakis, and J.-C. Latombe. Analysis of probabilistic roadmaps for path planning. In Proceedings of IEEE Conference on Robotics and Automation, volume 4, pp. 3020–3025, 1996.
L.E. Kavraki, F. Lamiraux, and C. Holleman. Towards planning for elastic objects. In Proceedings of Workshop on Algorithmic Foundations of Robotics, 1998.
L.E. Kavraki and J.-C. Latombe. Randomized preprocessing of configuration space for fast path planning. In Proceedings of IEEE Conference on Robotics and Automation, volume 3, pp. 2138–2145, 1994.
L.E. Kavraki and J.-C. Latombe. Probabilistic roadmaps for robot path planning. In K. Gupta and P. del Pobil, editors, Practical Motion Planning in Robotics: Current Approaches and Future Directions, pp. 33–53. John Wiley & Sons LTD, 1998.
L.E. Kavraki, J.-C. Latombe, R. Motwani, and P. Raghavan. Randomized query processing in robot motion planning. In Proceedings of the ACM Symposium on Theory of Computing, pp. 353–362, 1995.
L.E. Kavraki, J.-C. Latombe, R. Motwani, and P. Raghavan. Randomized query processing in robot path planning. Journal of Computer and System Science, 57(1):50–60, August 1998.
L.E. Kavraki, P. S̆vestka, J.-C. Latombe, and M.H. Overmars. Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transactions on Robotics and Automation, 12(4):566–580, August 1996.
O. Khatib. Real-time obstacle avoidance for manipulators and mobile robots. International Journal of Robotics Research, 5(1):90–98, 1986.
R. Kindel, D. Hsu, J.-C. Latombe, and S. Rock. Kinodynamic motion planning amidst moving obstacles. In Proceedings of IEEE Conference on Robotics and Automation, pp. 537–543, 2000.
D.E. Koditschek. Robot planning and control via potential functions. In The Robotics Review 1, pp. 349–367. MIT Press, 1989.
J.J. Kuffner, Jr. and S.M. LaValle. RRT-connect: An efficient approach to single-query path planning. In Proceedings of IEEE Conference on Robotics and Automation, pp. 995–1001, 2000.
J. C. Latombe. Robot Motion Planning. Kluwer Academic Publishers, Boston, 1991.
S. M. LaValle. Planning Algorithms. [Online], 1999–2003. Available at http://msl.cs.uiuc.edu/planning/.
S. M. LaValle and M. S. Branicky. On the relationship between classical grid search and probabilistic roadmaps. In Proceedings of Workshop on Algorithmic Foundations of Robotics, 2002.
S.M. LaValle and J.J. Kuffner, Jr. Randomized kinodynamic planning. In Proceedings of IEEE Conference on Robotics and Automation, pp. 473–479, 1999.
S.M. LaValle and J.J. Kuffner, Jr. Rapidly-exploring random trees: Progress and prospects. In Proceedings of Workshop on Algorithmic Foundations of Robotics, 2000.
S.M. LaValle, J.H. Yakey, and L.E. Kavraki. A probabilistic roadmap approach for systems with closed kinematic chains. In Proceedings of IEEE Conference on Robotics and Automation, pp. 1671–1676, 1999.
P. Leven and S. Hutchinson. Toward real-time path planning in changing environments. In Proceedings of Workshop on Algorithmic Foundations of Robotics, 2000.
P. Leven and S. Hutchinson. Real-time path planning in changing environments. International Journal of Robotics Research, 21(12):999–1030, December 2002.
P. Leven and S. Hutchinson. Using manipulability to bias sampling during the construction of probabilistic roadmaps. IEEE Transactions on Robotics and Automation, 19(6), December 2003.
T. Lozano-Pérez. Spatial planning: A configuration space approach. IEEE Transactions on Computers, February 1983.
E. Mazer, J.M. Ahuactzin, and P. Bessiere. The Ariadne’s clew algorithm. Journal of Artificial Intelligence Research, 9:295–316, 1998.
A. McLean and I. Mazon. Incremental roadmaps and global path planning in evolving industrial environments. In Proceedings of IEEE Conference on Robotics and Automation, pp. 101–107, 1996.
M. Mehrandezh and K. Gupta. Simultaneous path planning and free space exploration with skin sensor. In Proceedings of IEEE Conference on Robotics and Automation, pp. 3838–3843, 2002.
C. Nissoux, T. Simeon, and J-P. Laumond. Visibility based probabilistic roadmaps. In Proceedings of IEEE/RSJ Conference on Intelligent Robots and Systems, pp. 1316–1321, 1999.
M.H. Overmars and P. S̆vestka. A probabilistic learning approach to motion planning. In Proceedings of Workshop on Algorithmic Foundations of Robotics, pp. 19–37, 1994.
M.H. Overmars and P. S̆vestka. A paradigm for probabilistic path planning. Technical Report UU-CS-1995-22, Utrecht University, March 1995.
J. T. Schwartz, M. Sharir, and J. Hopcroft, editors. Planning, Geometry, and Complexity of Robot Motion. Ablex, Norwood, NJ, 1987.
D. Vallejo, C. Jones, and N.M. Amato. An adaptive framework for’ single shot’ motion planning. Technical Report TR99-024, Department of Computer Science, Texas A&M University, College Station, TX, October 1999.
S.A. Wilmarth, N.M. Amato, and P.F. Stiller. Motion planning for a rigid body using random networks on the medial axis of the free space. In Proceedings of ACM Symposium on Computational Geometry, pp. 173–180, 1999.
T. Yoshikawa. Manipulability of robotic mechanisms. International Journal of Robotics Research, 4(2):3–9, April 1985.
Y. Yu and K. Gupta. Sensor-based roadmaps for motion planning for articulated robots in unknown environments: Some experiments with an eye-in-hand system. In Proceedings of IEEE/RSJ Conference on Intelligent Robots and Systems, 1999.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Hutchinson, S., Leven, P. (2005). Planning Collision-Free Paths Using Probabilistic Roadmaps. In: Handbook of Geometric Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28247-5_23
Download citation
DOI: https://doi.org/10.1007/3-540-28247-5_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20595-1
Online ISBN: 978-3-540-28247-1
eBook Packages: Computer ScienceComputer Science (R0)