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Shared-Control-Based Bimanual Robot Manipulation

Science Robotics — jun 2019
Download the publication : 19_ScienceRobotics_preprint.pdf [22.1Mo]  
Human-centered environments provide affordances for and require the use of two-handed, or ``bimanual,'' manipulations. Robots that are designed to function in, and physically interact with, these environments have not been able to meet these requirements, because standard bimanual control approaches have not accommodated the diverse, dynamic, and intricate coordinations between two arms in order to complete bimanual tasks. In this work, we enable robots to more effectively perform bimanual tasks by introducing a bimanual shared-control method. The control method moves the robot's arms to mimic the operator's movements, but provides on-the-fly assistance to help the user complete tasks more easily. Our method utilizes a bimanual action vocabulary, constructed by analyzing how people perform two-hand manipulations, as the core abstraction level for reasoning about how to assist in bimanual shared-autonomy. The method infers which individual action from the bimanual action vocabulary is occurring using a sequence-to-sequence recurrent neural network architecture and turns on an assistance mode designed to help during the corresponding bimanual action. We demonstrate the effectiveness of our method through two user studies that show that novice users can control a robot to complete a range of complex manipulation tasks more successfully using our method compared to alternative approaches. We discuss the implications of our findings for real-world robot control scenarios and other related human-robot collaboration domains.

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BibTex references

@Article{RMGH19,
  author       = "Rakita, Daniel and Mutlu, Bilge and Gleicher, Michael and Hiatt, Laura",
  title        = "Shared-Control-Based Bimanual Robot Manipulation",
  journal      = "Science Robotics",
  month        = "jun",
  year         = "2019",
  doi          = "10.1126/scirobotics.aaw0955",
  url          = "http://graphics.cs.wisc.edu/Papers/2019/RMGH19"
}
 

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