Learning Hierarchical Control for Robust In-Hand Manipulation

@article{Li2020LearningHC,
  title={Learning Hierarchical Control for Robust In-Hand Manipulation},
  author={Tingguang Li and K. Srinivasan and Max Qing-Hu Meng and Wenzhen Yuan and Jeannette Bohg},
  journal={2020 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2020},
  pages={8855-8862}
}
  • Tingguang Li, K. Srinivasan, +2 authors Jeannette Bohg
  • Published 2020
  • Computer Science, Engineering
  • 2020 IEEE International Conference on Robotics and Automation (ICRA)
  • Robotic in-hand manipulation has been a longstanding challenge due to the complexity of modelling hand and object in contact and of coordinating finger motion for complex manipulation sequences. To address these challenges, the majority of prior work has either focused on model-based, low-level controllers or on model-free deep reinforcement learning that each have their own limitations. We propose a hierarchical method that relies on traditional, model-based controllers on the low-level and… CONTINUE READING

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