2024/07/18 by Tamon Miyake, Namiko Saito, Miyake, Tamon +7 · 2 citations
Medicine · #FOS: Computer and information sciences #Robotics (cs.RO) #Stroke Rehabilitation and Recovery
paper · pdf · doi:10.48550/arxiv.2407.13376
openalex publication_date 2024/07/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Caregiving is a vital role for domestic robots, especially the repositioning care has immense societal value, critically improving the health and quality of life of individuals with limited mobility. However, repositioning task is a challenging area of research, as it requires robots to adapt their motions while interacting flexibly with patients. The task involves several key challenges: (1) applying appropriate force to specific target areas; (2) performing multiple actions seamlessly, each requiring different force application policies; and (3) motion adaptation under uncertain positional conditions. To address these, we propose a deep neural network (DNN)-based architecture utilizing proprioceptive and visual attention mechanisms, along with impedance control to regulate the robot's movements. Using the dual-arm humanoid robot Dry-AIREC, the proposed model successfully generated motions to insert the robot's hand between the bed and a mannequin's back without applying excessive force, and it supported the transition from a supine to a lifted-up position. The project page is here: https://sites.google.com/view/caregiving-robot-airec/repositioning