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Learning inverse kinematics with structured prediction
2011
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
Learning inverse kinematics of robots with redundant degrees of freedom (DoF) is a difficult problem in robot learning. The difficulty lies in the non-uniqueness of the inverse kinematics function. Existing methods tackle non-uniqueness by segmenting the configuration space and building a global solution from local experts. The usage of local experts implies the definition of an oracle, which governs the global consistency of the local models; the definition of this oracle is difficult. We
doi:10.1109/iros.2011.6048552
fatcat:md57yhojqzb5ng7n3munafxjti