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During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness.
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Percolation
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D. Hsu, J. C. Latombe, and H. Kurniawati · 2006
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Planning Algorithms
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Molecular disassembly with RRT-like algorithms
J. Cortes, L. Jailet, and T. Simeon · 2007
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Cited alongside, same era.
Random Graphs
B. Bollobás · 2001
Cited alongside, same era.
Quasi-randomized path planning
M. S. Branicky, S. M. LaValle, K. Olson, and L. Yang · 2001
Cited alongside, same era.
Analysis of range search for random k-d trees
P. Chanzy, L. Devroye, and C. Zamora-Cura · 2001
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Probability and Random Processes
G. Grimmett and D. Stirzaker · 2001
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Randomized kinodynamic planning
S. M. LaValle and J. J. Kuffner · 2001
Cited alongside, same era.
M. Stilman, J. Schamburek, J. Kuffner, and T. Asfour · 2007
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A. R. Wade · 2007
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A. Yershova and S. M. LaValle · 2007
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M. Zucker, J. J. Kuffner, and M. S. Branicky · 2007
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An optimization approach to planning for mobile manipulation
D. Berenson, J. Kuffner, and H. Choset · 2008
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Anytime search in dynamic graphs
M. Likhachev, D. Ferguson, G. Gordon, A. Stentz, and S. Thrun · 2008
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Quantitative analysis of nearest-neighbors search in high-dimensional sampling-based motion planning
E. Plaku and L. E. Kavraki · 2008
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On heavy-tailed runtimes and restarts in rapidly-exploring random trees
N. A. Wedge and M.S. Branicky · 2008
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Motion planning in highly constrained spaces
A. Yershova and S. M. LaValle · 2008
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Experimental Robotics , chapter Path Planning for Autonomous Driving in Unknown Environments, pages 55–64
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Concentration of Measure for the Analysis of Randomized Algorithms
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Y. Kuwata, J. Teo, G. Fiore, S. Karaman, E. Frazzoli, and J.P. How · 2009
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S. M. LaValle and J. J. Kuffner · 2009
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Planning long dynamically-feasible maneuvers for autonomous vehicles
M. Likhachev and D. Ferguson · 2009
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The belief roadmap: Efficient planning in blief space by factoring the covariance
S. Prentice and N. Roy · 2009
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Asymptotic theory for the multidimensional random on-line nearest-neighbour graph
A. R. Wade · 2009
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Sampling-based path planning on configuration-space costmaps
L. Jaillet, J. Cortes, and T .Simeon · 2010
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Integration of path/manuever planning in complex environments for agile maneuvering UCAVs
E. Koyuncu, N.K. Ure, and G. Inalhan · 2010
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Bounds on tracking error using closed-loop rapidly-exploring random trees
B. Luders, S. Karaman, E. Frazzoli, and J. P. How · 2010
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Sampling-diagram automata: a tool for analyzing path quality in tree planners
O. Nechushtan, B. Raveh, and D. Halperin · 2010
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LQR-trees: Feedback motion planning via sums of squares verification
R. Tedrake, I. R. Manchester, M. M. Tobekin, and J. W. Roberts · 2010
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A voice-commandable robotic forklift working alongside humans in minimally-prepared outdoor environments
S. Teller, M. R. Walter, M. Antone, A. Correa, R. Davis, L. Fletcher, E. Frazzoli, J. Glass, J.P. How, A. S. Huang, J. Jeon, S. Karaman, B. Luders, N. Roy, and T. Sainath · 2010
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Rapidly-exploring roadmaps: Weighing exploration vs. reginement in optimal motion planning
R. Alterovitz, S. Patil, and A. Derbakova · 2011
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Addressing cost-space chasms in manipulation planning
D. Berenson, T. Simeon, and S. Srinivasa · 2011
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Rapidly-exploring random belief trees for motion planning under uncertainty
A. Bry and N. Roy · 2011
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Anytime motion planning using the RRT ∗
S. Karaman, M. Walter, A. Perez, E. Frazzoli, and S. Teller · 2011
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Bounding on rough terrain with the LittleDog robot
A. Shkolnik, M. Levashov, I. R. Manchester, and R. Tedrake · 2011
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