Center-of-Mass-based Robust Grasp Planning for Unknown Objects Using Tactile-Visual Sensors

@article{Feng2020CenterofMassbasedRG,
  title={Center-of-Mass-based Robust Grasp Planning for Unknown Objects Using Tactile-Visual Sensors},
  author={Qian Feng and Zhaopeng Chen and Jun Deng and Chunhui Gao and Jianwei Zhang and A. Knoll},
  journal={2020 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2020},
  pages={610-617}
}
An unstable grasp pose can lead to slip, thus an unstable grasp pose can be predicted by slip detection. A regrasp is required afterwards to correct the grasp pose in order to finish the task. In this work, we propose a novel regrasp planner with multi-sensor modules to plan grasp adjustments with the feedback from a slip detector. Then a regrasp planner is trained to estimate the location of center of mass, which helps robots find an optimal grasp pose. The dataset in this work consists of 1… Expand
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