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    IROS
    2008
    IEEE
    142views Robotics» more  IROS 2008»
    Probabilistic mapping of dynamic obstacles using Markov chains for replanning in dynamic environments
    15 years 4 months ago
    Probabilistic mapping of dynamic obstacles using Markov chains for replanning in dynamic environments
    Download  www.lsr.ei.tum.de
    — Robots acting in populated environments must be capable of safe but also time efficient navigation. Trying to completely avoid regions resulting from worst case predictions of...
    Florian Rohrmüller, Matthias Althoff, Dirk Wo...
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    ICGA
    1993
    96views Optimization» more  ICGA 1993»
    Dynamic Control of Genetic Algorithms in a Noisy Environment
    14 years 11 months ago
    Dynamic Control of Genetic Algorithms in a Noisy Environment
    Download  manip.crhc.uiuc.edu
    In this paper, we present e cient algorithms for adjusting con guration parameters of genetic algorithms that operate in a noisy environment. Assuming that the population size is ...
    Akiko N. Aizawa, Benjamin W. Wah
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    IJSR
    2010
    150views more  IJSR 2010»
    Real-time Motion Tracking from a Mobile Robot
    14 years 8 months ago
    Real-time Motion Tracking from a Mobile Robot
    Download  cres.usc.edu
    — A mobile robot needs to perceive the motions of external objects to perform tasks successfully in a dynamic environment. We propose a set of algorithms for multiple motion trac...
    Boyoon Jung, Gaurav S. Sukhatme
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    AUTOMATICA
    2011
    241views Artificial Intelligence» more  AUTOMATICA 2011»
    Distributed dynamic programming for discrete-time stochastic control, and idempotent algorithms
    14 years 5 months ago
    Distributed dynamic programming for discrete-time stochastic control, and idempotent algorithms
    Download  maeresearch.ucsd.edu
    Previously, idempotent methods have been found to be extremely fast for solution of dynamic programming equations associated with deterministic control problems. The original meth...
    William M. McEneaney
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    IROS
    2008
    IEEE
    156views Robotics» more  IROS 2008»
    Bayesian state estimation and behavior selection for autonomous robotic exploration in dynamic environments
    15 years 4 months ago
    Bayesian state estimation and behavior selection for autonomous robotic exploration in dynamic environments
    Download  www.lsr.ei.tum.de
    — In order to be truly autonomous, robots that operate in natural, populated environments must have the ability to create a model of these unpredictable dynamic environments and ...
    Georgios Lidoris, Dirk Wollherr, Martin Buss
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