Paper:
Dressing Assistance Method for Long-Sleeved Shirts Using End-to-End Motion Prediction
Yutaka Takase*
, Keisuke Onda**, and Kimitoshi Yamazaki***
*Faculty of Engineering, Shinshu University
4-17-1 Wakasato, Nagano, Nagano 380-8553, Japan
**Department of Engineering, Shinshu University
4-17-1 Wakasato, Nagano, Nagano 380-8553, Japan
***Department of Robotics, Graduate School of Engineering, Tohoku University
6-6-01 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8579, Japan
This study presents a novel method for helping hemiplegic patients put on a long-sleeved shirt. Our analysis specifically focuses on the behaviors of patients with hemiplegia in the latter half of the dressing phase, which involves moving the garment to the healthy side after dressing the paralyzed side. We propose a novel method to assist this movement. A key aspect of the proposed method is the inclusion of a module capable of predicting the target position of a robot’s end effector using time-series depth images. By combining this module with force-based control, a single-armed robot helps a wearer manipulate their garment according to their movements. Experiments utilizing an articulated manipulator demonstrate the effectiveness of the proposed method.

Dressing assistance with prediction
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