frontiers in Neurorobotics

Design of Muscle Reflex Control for Upright Standing Push-Recovery Based on a Series Elastic Robot Ankle Joint

Yuyang Cao, Kui Xiang, Biwei Tang, Zhaojie Ju, Muye Pang

School of Automation, Intelligent System Research Institute, Wuhan University of Technology, Wuhan


muscle reflex, ankle joint, upright standing, push-recovery, series elastic actuator


In physical human–robot interaction environment, ankle joint muscle reflex control remains significant and promising in human bipedal stance. The reflex control mechanism contains rich information of human joint dynamic behavior, which is valuable in the application of real-time decoding motion intention. Thus, investigating the human muscle reflex mechanism is not only meaningful in human physiology study but also useful for the robotic system design in the field of human–robot physical interaction. In this paper, a specialized ankle joint muscle reflex control algorithm for human upright standing push-recovery is proposed. The proposed control algorithm is composed of a proportional-derivative (PD)-like controller and a positive force controller, which are employed to mimic the human muscle stretch reflex and muscle tendon force reflex, respectively. Reflex gains are regulated by muscle activation levels of contralateral ankle muscles. The proposed method was implemented on a self-designed series elastic robot ankle joint (SERAJ), where the series elastic actuator (SEA) has the potential to mimic human muscle–tendon unit (MTU). During the push-recovery experimental study, the surface electromyography (sEMG), ankle torque, body sway angle, and velocity of each subject were recorded in the case where the SERAJ was unilaterally kneed on each subject. The experimental results indicate that the proposed muscle reflex control method can easily realize upright standing push-recovery behavior, which is analogous to the original human behavior.

Moticon's Summary

This study is concerned with the reflex control mechanism of the ankle joint in the context of human robot-robot interactions for example in ankle prosthesis. Specifically, the authors introduce a control algorithm mimicking the human reflex control mechanism of the ankle joint. The adequacy of the proposed control algorithm was further demonstrated with a self-designed actuation device. Here Moticon sensor insoles were used to obtain data which was used to compute resulting ankle torques. The authors found their algorithm to be adequate to control stance when using a robotic ankle joint.

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