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» Planning with Partial Preference Models
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FSR
2007
Springer
135views Robotics» more  FSR 2007»
14 years 2 months ago
State Space Sampling of Feasible Motions for High Performance Mobile Robot Navigation in Highly Constrained Environments
Sampling in the space of controls or actions is a well-established method for ensuring feasible local motion plans. However, as mobile robots advance in performance and competence ...
Thomas M. Howard, Colin J. Green, Alonzo Kelly
WSC
2007
13 years 10 months ago
Simulation-aided path planning of UAV
The problem of path planning for Unmanned Aerial Vehicles (UAV) with a tracking mission, when some a priori information about the targets and the environment is available can in s...
Farzad Kamrani, Rassul Ayani
PAMI
2000
129views more  PAMI 2000»
13 years 8 months ago
Constraint-Based Sensor Planning for Scene Modeling
We describe an automated scene modeling system that consists of two components operating in an interleaved fashion: an incremental modeler that builds solid models from range imag...
Michael K. Reed, Peter K. Allen
ICRA
2010
IEEE
163views Robotics» more  ICRA 2010»
13 years 7 months ago
Exploiting domain knowledge in planning for uncertain robot systems modeled as POMDPs
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...
Salvatore Candido, James C. Davidson, Seth Hutchin...
JAIR
2000
152views more  JAIR 2000»
13 years 8 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht