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Human-Robot Cooperative Transport

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Project Motivation

As robots become more capable assistants, it is important that they be able to collaborate leveraging implicit communication and situational awareness. This project of human-robot cooperative transport exemplifies a scenario where the robot serves as a valuable teammate but it is untenable for the human to issue constant explicit commands. The robot instead must be able to observe the human as well as the environment and predict where the human is trying to go.  In a centralized system (all robots), a single governing controller would specify how every agent should move to transport the object to the goal location and 'waste' as little energy as possible compressing or stretching the object during transport. This compressing or stretching can be characterized as interaction forces (forces that don't contribute to motion), and minimizing these is often considered a metric for efficient transport. Therefore, the goal is to have the robot leverage its knowledge of the human and environment to transport efficiently. 

Research Objectives

Research objectives include:

  • Develop robotic platform capable of modeling humans intended motion from measured quantity
  • Utilize human observation and the surrounding environment to predict the desired motion
  • Understand how to grasp/re-grasp objects with the human leader for successful placement

Current Students

Related Publications


Active User Studies

Preliminary Work: The intended pose of the human leader is estimated implicitly by observing the human's head direction, the applied wrench through the rigid carried object, the human steps, the twist of the carried object and the surrounding obstacles. Each of the above quantities can be intuitively related to the expected pose by an integrator (e.g. twist integrates to pose, wrench integrated twice predicts pose) with surrounding obstacles being constraints. However the combination of all of these terms is non-trivial and is the main contribution of this work.