Abstract

Revealing human internal control mechanisms during environmental interaction remains paramount and helpful in solving issues related to human-robot interaction. Muscle reflexes, which can directly and rapidly modify the dynamic behavior of joints, are the fundamental control loops of the Central Nervous System. This study investigates the calf muscle reflex control in the “ankle strategy” for human push-recovery movement. A time-increasing searching method is proposed to evaluate the feasibility of the reflex model in terms of predicting real muscle activations. Constraints with physiological implications are imposed to find the appropriate reflex gains. The experimental results show that the reflex model fits over 90% of the forepart of muscle activation. With the increasing of time, the Variance Accounted For (VAF) values drop to below 80% and reflex gains lose the physiology meaning. By dividing the muscle activation into two parts, the reflex formula is still workable for the rest part, with different gains and lower VAF values. This result may indicate that reflex control could more likely dominate the forepart of the push-recovery motion and an analogous control mechanism is still feasible for the rest of the motion part, with different gains. The proposed method provides an alternative way to obtain the human internal control mechanism desired for human-robot interaction task.

Highlights

  • Human-robot interaction, especially physical interaction, has recently drawn great and increasing attention [1]

  • As soon as the disturbance is exerted on the back of the subject, the joint angular velocity increases quickly in the negative direction, and the body of the subject leans ankle joint angular velocity increases quickly in the negative direction, and the body of the subject forward

  • According to the data comprising90.0/95.3(0.045 this figure, it can60.1/80.1(

Read more

Summary

Introduction

Human-robot interaction, especially physical interaction, has recently drawn great and increasing attention [1]. Many wearable ankle joint robotic devices and control methods have been developed to enhance human locomotion ability [2,3]. For robot-assisted implementation, it is suggested that robot devices should not override human control, but rather involve the user in the control [4]. Revealing the human internal control mechanism facing the physical interaction task shows an alternative way to provide a reference for robotic control system design [5]. Joint-level response to physical interaction with humans is unique to present-day robotic systems, in which central control and stiff joint are widely adopted. Despite having achieved great breakthroughs in whole-body control of robots in different tasks, it depends heavily on high-accuracy sensation, Appl.

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.