Iterative learning of grasp adaptation through human corrections

  title={Iterative learning of grasp adaptation through human corrections},
  author={Eric L. Sauser and Brenna Argall and Giorgio Metta and Aude Billard},
  journal={Robotics and Autonomous Systems},
In the context of object interaction and manipulation, one characteristic of a robust grasp is its ability to comply with external perturbations applied to the grasped object while still maintaining the grasp. In this work, we introduce an approach for grasp adaptation which learns a statistical model to adapt hand posture solely based on the perceived contact between the object and fingers. Using a multi-step learning procedure, the model dataset is built by first demonstrating an initial hand… CONTINUE READING
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Learning nonlinear multivariate dynamics of motion in robotic manipulators

  • E. Gribovskaya, S. Khansari Zadeh, A. Billard
  • International Journal of Robotics Research (2011…
  • 2012
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