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» Path planning using learned constraints and preferences
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ICRA
2010
IEEE
142views Robotics» more  ICRA 2010»
14 years 8 months ago
Learning and planning high-dimensional physical trajectories via structured Lagrangians
— We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to s...
Paul Vernaza, Daniel D. Lee, Seung-Joon Yi
94
Voted
ATAL
2011
Springer
13 years 9 months ago
Learning action models for multi-agent planning
In multi-agent planning environments, action models for each agent must be given as input. However, creating such action models by hand is difficult and time-consuming, because i...
Hankz Hankui Zhuo, Hector Muñoz-Avila, Qian...
CP
2005
Springer
15 years 3 months ago
Speeding Up Constrained Path Solvers with a Reachability Propagator
Constrained path problems have to do with finding paths in graphs subject to constraints. One way of constraining the graph is by enforcing reachability on nodes. For instance, i...
Luis Quesada, Peter Van Roy, Yves Deville
70
Voted
IROS
2008
IEEE
91views Robotics» more  IROS 2008»
15 years 4 months ago
Replanning: A powerful planning strategy for hard kinodynamic problems
— A series of kinodynamic sampling-based planners have appeared over the last decade to deal with high dimensional problems for robots with realistic motion constraints. Yet, of...
Konstantinos I. Tsianos, Lydia E. Kavraki
SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
14 years 11 months ago
Making Time-Series Classification More Accurate Using Learned Constraints
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh