Demonstration: OCRA - A Kinematic Retargeting Algorithm for Expressive Whole-Arm Teleoperation

2024

Miscellaneous

hi

Traditional teleoperation systems focus on controlling the pose of the end-effector (task space), often neglecting the additional degrees of freedom present in human and many robotic arms. This demonstration presents the Optimization-based Customizable Retargeting Algorithm (OCRA), which was designed to map motions from one serial kinematic chain to another in real time. OCRA is versatile, accommodating any robot joint counts and segment lengths, and it can retarget motions from human arms to kinematically different serial robot arms with revolute joints both expressively and efficiently. One of OCRA's key features is its customizability, allowing the user to adjust the emphasis between hand orientation error and the configuration error of the arm's central line, which we call the arm skeleton. To evaluate the perceptual quality of the motions generated by OCRA, we conducted a video-watching study with 70 participants; the results indicated that the algorithm produces robot motions that closely resemble human movements, with a median rating of 78/100, particularly when the arm skeleton error weight and hand orientation error are balanced. In this demonstration, the presenter will wear an Xsens MVN Link and teleoperate the arms of a NAO child-size humanoid robot to highlight OCRA's ability to create intuitive and human-like whole-arm motions.

@misc{Mohan24-CORLD-Algorithm,
  title = {Demonstration: {OCRA} - A Kinematic Retargeting Algorithm for Expressive Whole-Arm Teleoperation},
  author = {Mohan, Mayumi and Kuchenbecker, Katherine J.},
  howpublished = {Hands-on demonstration presented at the Conference on Robot Learning (CoRL)},
  address = {Munich, Germany},
  month = nov,
  year = {2024},
  doi = {},
  month_numeric = {11}
}