LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information
Author:
Affiliation:
1. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,
2. University of California, Berkeley, CA, USA
Abstract
Publisher
SAGE Publications
Subject
Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modeling and Simulation,Software
Link
http://journals.sagepub.com/doi/pdf/10.1177/0278364911406562
Reference34 articles.
1. The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
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