Shared Dynamic Curves: A Shared-Control Telemanipulation Method for Motor Task Training
2018 ACM/IEEE International Conference on Human Robot Interaction — mar 2018
In this paper, we present a novel shared-control telemanipulation method that is designed to incrementally improve a user's motor
ability. Our method initially corrects for the user's suboptimal control trajectories, gradually giving the user more direct control over a
series of training trials as he/she naturally gets more accustomed to the task. Our shared-control method, called Shared Dynamic Curves,
blends suboptimal user translation and rotation control inputs with
known translation and rotation paths needed to complete a task.
Shared Dynamic Curves provide a translation and rotation path
in space along which the user can easily guide the robot, and this
curve can bend and ?ex in real-time as a dynamical system to pull
the user's motion gracefully toward a goal. We show through a user
study that Shared Dynamic Curves a?ords e?ective motor learning
on certain tasks compared to alternative training methods. We discuss our fndings in the context of shared control and speculate on
how this method could be applied in real-world scenarios such as
job training or stroke rehabilitation.
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BibTex references
@InProceedings{RMGH18, author = "Rakita, Daniel and Mutlu, Bilge and Gleicher, Michael and Hiatt, Laura", title = "Shared Dynamic Curves: A Shared-Control Telemanipulation Method for Motor Task Training", booktitle = "2018 ACM/IEEE International Conference on Human Robot Interaction", month = "mar", year = "2018", publisher = "ACM", doi = "10.1145/3171221.3171278", url = "http://graphics.cs.wisc.edu/Papers/2018/RMGH18" }