Strategies for human-in-the-loop robotic grasping

  • Authors:

  • Adam Eric Leeper;Kaijen Hsiao;Matei Ciocarlie;Leila Takayama;David Gossow

  • Affiliations:

  • Willow Garage, Inc. and Stanford University, Menlo Park, CA, USA;Willow Garage, Inc., Menlo Park, CA, USA;Willow Garage, Inc., Menlo Park, CA, USA;Willow Garage, Inc., Menlo Park, CA, USA;Technische Universität München, Munich, Germany

  • Venue:
  • HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
  • Year:
  • 2012

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Abstract

Human-in-the loop robotic systems have the potential to handle complex tasks in unstructured environments, by combining the cognitive skills of a human operator with autonomous tools and behaviors. Along these lines, we present a system for remote human-in-the-loop grasp execution. An operator uses a computer interface to visualize a physical robot and its surroundings, and a point-and-click mouse interface to command the robot. We implemented and analyzed four different strategies for performing grasping tasks, ranging from direct, real-time operator control of the end-effector pose, to autonomous motion and grasp planning that is simply adjusted or confirmed by the operator. Our controlled experiment (N=48) results indicate that people were able to successfully grasp more objects and caused fewer unwanted collisions when using the strategies with more autonomous assistance. We used an untethered robot over wireless communications, making our strategies applicable for remote, human-in-the-loop robotic applications.