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    2007
    136views Robotics» more  RSS 2007»
    The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
    14 years 11 months ago
    The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
    Download  www.ieor.berkeley.edu
    — We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
    Ron Alterovitz, Thierry Siméon, Kenneth Y. ...
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    2007
    145views Robotics» more  RSS 2007»
    Semantic Modeling of Places using Objects
    14 years 11 months ago
    Semantic Modeling of Places using Objects
    Download  www.roboticsproceedings.org
    — While robot mapping has seen massive strides , higher level abstractions in map representation are still not widespread. Maps containing semantic concepts such as objects and l...
    Ananth Ranganathan, Frank Dellaert
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    2007
    135views Robotics» more  RSS 2007»
    Learning omnidirectional path following using dimensionality reduction
    14 years 11 months ago
    Learning omnidirectional path following using dimensionality reduction
    Download  www.roboticsproceedings.org
    Abstract— We consider the task of omnidirectional path following for a quadruped robot: moving a four-legged robot along any arbitrary path while turning in any arbitrary manner....
    J. Zico Kolter, Andrew Y. Ng
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    2007
    147views Robotics» more  RSS 2007»
    Discrete Search Leading Continuous Exploration for Kinodynamic Motion Planning
    14 years 11 months ago
    Discrete Search Leading Continuous Exploration for Kinodynamic Motion Planning
    Download  www.roboticsproceedings.org
    Abstract— This paper presents the Discrete Search Leading continuous eXploration (DSLX) planner, a multi-resolution approach to motion planning that is suitable for challenging p...
    Erion Plaku, Lydia E. Kavraki, Moshe Y. Vardi
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    2007
    152views Robotics» more  RSS 2007»
    Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
    14 years 11 months ago
    Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
    Download  www.vision.caltech.edu
    Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
    Anelia Angelova, Larry Matthies, Daniel M. Helmick...
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