Trajectory clustering and stochastic approximation for robot programming by demonstration

@article{Aleotti2005TrajectoryCA,
  title={Trajectory clustering and stochastic approximation for robot programming by demonstration},
  author={Jacopo Aleotti and Stefano Caselli},
  journal={2005 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2005},
  pages={1029-1034}
}
This paper describes the trajectory learning component of a programming by demonstration (PbD) system for manipulation tasks. In case of multiple user demonstrations, the proposed approach clusters a set of hand trajectories and recovers smooth robot trajectories overcoming sensor noise and human motion inconsistency problems. More specifically, we integrate a geometric approach for trajectory clustering with a stochastic procedure for trajectory evaluation based on hidden Markov models… CONTINUE READING
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