Construction of a geometric 3-D model from sensor measurements collected during compliant motion

Springer Tracts in Advanced Robotics(2006)

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摘要
This paper describes the construction of a 3-D model from the identification of geometrical parameters of polyhedral objects during a force-controlled task. Following improvements with respect to the state of the art axe made: (i) creation of a 3-D model from a previously unknown environment, (ii) force estimation for feedback to a force controller or for monitoring contact forces, (iii) reduction of the number of modelling parameters, leading to computational reduction and more accurate geometric descriptions.
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关键词
adaptive control,maximum likelihood estimate,neural network,robot control,bayesian statistics,hidden markov model,geometric model
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