Personalized Assist-As-Needed Dressing Assistance Robot without Human Modeling using Rowat-Selverston CPG Controller - Archive ouverte HAL
Article Dans Une Revue Advanced Robotics Année : 2024

Personalized Assist-As-Needed Dressing Assistance Robot without Human Modeling using Rowat-Selverston CPG Controller

Résumé

Dressing is a critical component of Activity of Daily Living (ADLs). The development of assistive technology for dressing tasks is urgently needed from the viewpoint of privacy, for example, to prevent the wearer from being seen in the nude. Despite their importance, these technologies are underutilized in garment donning compared to other ADLs. The reasons for the lack of utilization of assistive technology are that the task is complex, as it involves handling individuals with large individual differences in height and symptoms and requires manipulation of flexible clothing. Addressing these variances presents a formidable academic challenge. Our previous study identified periodic patterns in human movements during robot-assisted dressing and noted individual variability in these patterns. Capitalizing on this finding, we propose a novel control strategy for a robot that adapts to individual needs during dressing, employing the "Assist-As-Needed" (AAN) principle from physical therapy. The proposed control method uses Central Pattern Generators (CPG) that can be synchronously controlled in response to external forces, enabling model-free control without human modeling. We utilize the Rowat-Selverston CPG model, which is recognized for its adaptive response to human motions in human-robot interactions such as with handshaking robots. A simulator of the Rowat-Selverston CPG was created. The output of the CPG was confirmed by inputting the data set obtained in previous studies, and the parameters were adjusted. The CPG output was then applied to the recorded target joint trajectory for the dressing assistance. We prepared a replay of the default trajectory, a trajectory with simple harmonic motion applied, and a trajectory with CPG output applied, and confirmed whether individual adaptation according to the AAN was possible through subject experiments. The experimental results showed that the Rowat-Selverston CPG control method enables individual adaptive dressing assistance according to the AAN principle. This study summarizes these methods and results and contributes to the realization of an individually adaptive system that follows the AAN principle, especially in developing assistive technology.
Fichier non déposé

Dates et versions

hal-04674349 , version 1 (21-08-2024)

Identifiants

  • HAL Id : hal-04674349 , version 1

Citer

Kakeru Yamasaki, Shibata Tomohiro, Patrick Henaff. Personalized Assist-As-Needed Dressing Assistance Robot without Human Modeling using Rowat-Selverston CPG Controller. Advanced Robotics, In press. ⟨hal-04674349⟩
34 Consultations
0 Téléchargements

Partager

More