Detail Cantuman

Current-pressure-position triple-loop feedback control of electro-hydrostatic
actuators for humanoid robots
Tianyi Ko , Hiroshi Kaminaga and Yoshihiko Nakamura
Depar tment of M echano -I nformatics, Graduate S chool of I nformation S cience and Technology, The Universit y of Tok yo, Bunk yo -Ku, Tok yo, Japan
ABSTR AC T
To overcome the tradeoff between torque density and response of the backdrivable actuators, actuation by electro-hydrostatic actuators (EHA) is effective. While their backdrivability and energy efficiency was shown in the previous studies, their closed-loop dynamic behavior was not discussed in detail. In this paper, we present the analysis and experimental evaluation of the force control performance of the electro-hydrostatic actuator for the humanoid robot ‘Hydra’. We first present a simplified model of EHA and show that EHA can be simplified as a mass-spring-damper model if all values such as pump torque/velocity and fluid pressure/flow-rate are expressed in the equivalent value seen from the actuator. We also show the comparison between the model and experimentally acquired open-loop dynamic behavior. Then, the evaluation on the force measurement and control performance is shown. The static friction on the rod-seal was 0.46% of the maximum piston force, and with additional strain gauge information, the error can be reduced to 0.28% of the maximum force. We also show that our developed EHA has a pressure control bandwidth of 100 Hz in the fixed piston configuration, which is higher than other state-of-the-art series elastic actuators. In the last of paper, the joint level position and torque control performance of Hydra is examined.
KEY WORDS
Ac t u ato r ; EH A ; hyd rau l i c ; fo rce control; backdrivabilit y

Reviewing high-level control techniques on robot-assisted upper-limb
rehabilitation
Qing Miaoa,b, Mingming Zhangb, Jinghui Caoc and Sheng Q. Xied
aSchool of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, People’s Republic of China; bDepartment of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, People’s Republic of China; cDepartment of Mechanical Engineering, The University of Auckland, Auckland, New Zealand; dSchool of Electronic and Electrical Engineering, University of Leeds, Leeds, UK
ABSTR AC T
This paper presents a comprehensive review of high-level control techniques for upper-limb robotic training. It aims to compare and discuss the potentials of these different control algorithms, and specify future research direction. Included studies mainly come from selected papers in four review articles. To make selected studies complete and comprehensive, especially some recently-developed upper-limb robotic devices, a search was further conducted in IEEE Xplore, Google Scholar, Scopus
and Web of Science using keywords (‘upper limb*’ or ‘upper body*’) and (‘rehabilitation*’ or ‘treatment*’) and (‘robot*’ or ‘device*’ or ‘exoskeleton*’). The search is limited to English-language articles published between January 2013 and December 2017. Valuable references in related publications were also screened. Comparative analysis shows that high-level interaction control strategies can be implemented in a range of methods, mainly including impedance/admittance based strategies, adaptive control techniques, and physiological signal control. Even though the potentials of existing interactive control strategies have been demonstrated, it is hard to identify the one leading to maximum encouragement from human users. However, it is reasonable to suggest that future studies should combine different control strategies to be application specific, and deliver appropriate robotic assistance based on physical disability levels of human users.
KEY WORDS
Interactive control; upper-limb; robot; rehabilitation

Unsupervised embrace pose recognition method for stuffed-toy robot
Nutnaree Kleawsirikul a, Hironori Mitakeb and Shoichi Hasegawab
aDepartment of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Japan; bLaboratory for Future Interdisciplinary Research of Science and Technology, Tokyo Institute of Technology, Yokohama, Japan
ABSTR AC T
This paper presents a new approach to model and recognize embrace interaction based on an embrace-comfortable fabric-based touchpad attached to a stuffed-toy robot with k-mean clustering of location-based features. Evaluation of the method demonstrated its ability to recognize embrace poses in new users with a suitable number of clusters. Consequently, the proposed class assignment method, which assigned classes based on the most common patterns, was used to determine the number of clusters in the model selection experiment. The experimental results showed that the selected model could obtain sufficient recognition performance, which contributed to a guideline for model selection, based directly on variations of embraces without requiring ground truths. This guideline could potentially be applied to different target populations and definitions of the embrace pose.
KEY WORDS
Embrace recognition; embrace interaction; k-means; touch sensor; soft-stuffed robot