Date pending, cs.ROJ/K move · Enter open · S save
Hiroshi Atsuta, Hisashi Ishihara, Minoru Asada
Symbiotic Intelligent Systems Research Center, Institute for Open and Transdisciplinary Research Initiatives, The University of Osaka, Suita, Osaka, Japan · College of Arts and Design, Ritsumeikan University, Kyoto, Japan · International Professional University of Technology in Osaka, Umeda, Kita-ku, Osaka, Japan+1
Pneumatically-actuated anthropomorphic robots with high degrees of freedom (DOF) offer significant potential for physical human-robot interaction. However, precise control of pneumatic actuators is challenging due to their inherent nonlinearities. This paper presents the development of a compact 13-DOF upper-body humanoid robot. To assess the feasibility of an effective controller, we first investigate its key dynamic properties, such as actuation time delays, and confirm that its behavior is reproducible across repeated trials. Leveraging this reproducibility, we implement a preliminary data-driven controller for a 4-DOF arm subsystem based on a multilayer perceptron with explicit time delay compensation. The network was trained on random movement data to generate pressure commands for tracking arbitrary trajectories. In comparative evaluations on this subsystem, the data-driven controller achieved lower tracking errors than a traditional PID controller. This result suggests that data-driven approaches are a promising option for controlling complex, high-DOF pneumatic robots.