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» An Algorithm for Probabilistic Least-Commitment Planning
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ATAL
2010
Springer
14 years 10 months ago
Merging example plans into generalized plans for non-deterministic environments
We present a new approach for finding generalized contingent plans with loops and branches in situations where there is uncertainty in state properties and object quantities, but ...
Siddharth Srivastava, Neil Immerman, Shlomo Zilber...
ICRA
2007
IEEE
156views Robotics» more  ICRA 2007»
15 years 4 months ago
Multipartite RRTs for Rapid Replanning in Dynamic Environments
Abstract— The Rapidly-exploring Random Tree (RRT) algorithm has found widespread use in the field of robot motion planning because it provides a single-shot, probabilistically c...
Matthew Zucker, James J. Kuffner, Michael S. Brani...
PKDD
2009
Springer
102views Data Mining» more  PKDD 2009»
15 years 4 months ago
Relevance Grounding for Planning in Relational Domains
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Tobias Lang, Marc Toussaint
AIPS
2006
14 years 11 months ago
Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle
In this paper, we present a motion planning framework for a fully deployed autonomous unmanned aerial vehicle which integrates two sample-based motion planning techniques, Probabi...
Mariusz Wzorek, Patrick Doherty
CORR
2010
Springer
134views Education» more  CORR 2010»
14 years 9 months ago
Incremental Sampling-based Algorithms for Optimal Motion Planning
During the last decade, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs), have been shown to work well in practice and to po...
Sertac Karaman, Emilio Frazzoli