Publications on Feedback Motion Planning

Simplicial Dijkstra and A* algorithms for optimal feedback planning. D. Yershov and S. M. LaValle. In Proceedings IEEE International Conference on Intelligent Robots and Systems, 2011. [pdf].

Motion planning: Wild frontiers. S. M. LaValle. IEEE Robotics and Automation Society Magazine, 18(2):108--118, 2011. [pdf].

Rendezvous wihtout coordinates. J. Yu, D. Liberzon, and S. M. LaValle. IEEE Transactions on Automatic Control, 57(2):421--434, 2012. [pdf].

Simple and efficient algorithms for computing smooth, collision-free feedback laws over given cell decompositions. S. R. Lindemann and S. M. LaValle. International Journal of Robotics Research, 28(5):600--621, 2009. [pdf].

Rendezvous without coordinates. J. Yu, D. Liberzon, and S. M. LaValle. In Proceedings IEEE Conference Decision and Control, pages 1803--1808, 2008. [pdf].

Chapter 8: Feedback Motion Planning, Planning Algorithms. S. M. LaValle. Cambridge University Press, Cambridge, U.K., 2006. [pdf] [Entire Book].

Real time feedback control for nonholonomic mobile robots with obstacles. S. R. Lindemann, I. I. Hussein, and S. M. LaValle. In Proceedings IEEE Conference Decision and Control, 2006. [pdf].

Computing smooth feedback plans over cylindrical algebraic decompositions. S. R. Lindemann and S. M. LaValle. In Proceedings Robotics: Science and Systems, 2006. [pdf].

Smoothly blending vector fields for global robot navigation. S. R. Lindemann and S. M. LaValle. In Proceedings IEEE Conference Decision and Control, pages 3353--3559, 2005. [pdf].

The sampling-based neighborhood graph: A framework for planning and executing feedback motion strategies. L. Yang and S. M. LaValle. IEEE Transactions on Robotics and Automation, 20(3):419--432, June 2004. [pdf].

Algorithms for computing numerical optimal feedback motion strategies. S. M. LaValle and P. Konkimalla. International Journal of Robotics Research, 20(9):729--752, September 2001. [pdf].

An improved random neighborhood graph approach. L. Yang and S. M. LaValle. In Proceedings IEEE International Conference on Robotics and Automation, pages 254--259, 2002. [pdf].

A framework for planning feedback motion strategies based on a random neighborhood graph. L. Yang and S. M. LaValle. In Proceedings IEEE International Conference on Robotics and Automation, pages 544--549, 2000. [pdf].

Efficient computation of optimal navigation functions for nonholonomic planning. P. Konkimalla and S. M. LaValle. In Proceedings First IEEE International Workshop on Robot Motion and Control, pages 187--192, 1999. [pdf].

Numerical computation of optimal navigation functions on a simplicial complex. S. M. LaValle. In P. K. Agarwal, L. E. Kavraki, and M. T. Mason, editors, Robotics: The Algorithmic Perspective, pages 339--350. A K Peters, Wellesley, MA, 1998. [pdf].

Optimizing robot motion strategies for assembly with stochastic models of the assembly process. R. Sharma, S. M. LaValle, and S. A. Hutchinson. IEEE Trans. on Robotics and Automation, 12(2):160--174, April 1996. [pdf].

Optimal motion planning for multiple robots having independent goals. S. M. LaValle and S. A. Hutchinson. IEEE Trans. on Robotics and Automation, 14(6):912--925, December 1998. [pdf].

An objective-based framework for motion planning under sensing and control uncertainties. S. M. LaValle and S. A. Hutchinson. International Journal of Robotics Research, 17(1):19--42, January 1998. [pdf].

On motion planning in changing, partially-predictable environments. S. M. LaValle and R. Sharma. International Journal of Robotics Research, 16(6):775--805, December 1997. [pdf].

Motion planning in stochastic environments: Theory and modeling issues. S. M. LaValle and R. Sharma. In Proceedings IEEE International Conference on Robotics and Automation, pages 3057--3062, 1995. [pdf].

Motion planning in stochastic environments: Applications and computational issues. S. M. LaValle and R. Sharma. In Proceedings IEEE International Conference on Robotics and Automation, pages 3063--3068, 1995. [pdf].

A game-theoretic framework for robot motion planning. S. M. LaValle. PhD thesis, University of Illinois, Urbana, IL, July 1995. [pdf].

An objective-based stochastic framework for manipulation planning. S. M. LaValle and S. A. Hutchinson. In Proceedings IEEE/RSJ/GI International Conference on Intelligent Robots and Systems, pages 1772--1779, September 1994. [pdf].

Robot motion planning in a changing, partially predictable environment. S. M. LaValle and R. Sharma. In Proceedings IEEE International Symposium on Intelligent Control, pages 261--266, August 1994. [pdf].