This paper describes the design, development, modeling, and control of a robotic platform developed for the characterization of mechanical impedance and reflex responses of the ankle in 2 degrees-of-freedom (DOF): sagittal (dorsiflexion-plantarflexion) and frontal plane (inversion-eversion). The platform, controlled actively along both DOFs, is capable of producing rapid and strong perturbations up to an angular speed of 200°/s and peak torque of 400 Nm. This enables study of ankle impedance characteristics even during extreme task conditions such as running. The platform is designed to provide perturbations to the ankle up to an angle of 20° in sagittal plane and 10° in frontal plane, which is sufficient for all possible configurations of the ankle during postural balance and stance phase of walking. These characteristics of the platform make it ideal for both impedance and reflex characterization along both DOFs of the ankle. The platform’s performance of position control is validated under varying loads simulating various conditions of posture and locomotion. The platform’s orientation accuracy in both sagittal and frontal planes is established for various input signals including slow sinusoid inputs and rapid ramp perturbations. Implications for future ankle studies to estimate neuro-mechanical characteristics and applications to assistive and prosthetic devices are discussed.
- Dynamic Systems and Control Division
Development of a Multiple Axis Robotic Platform for Ankle Studies
Nalam, V, & Lee, H. "Development of a Multiple Axis Robotic Platform for Ankle Studies." Proceedings of the ASME 2016 Dynamic Systems and Control Conference. Volume 1: Advances in Control Design Methods, Nonlinear and Optimal Control, Robotics, and Wind Energy Systems; Aerospace Applications; Assistive and Rehabilitation Robotics; Assistive Robotics; Battery and Oil and Gas Systems; Bioengineering Applications; Biomedical and Neural Systems Modeling, Diagnostics and Healthcare; Control and Monitoring of Vibratory Systems; Diagnostics and Detection; Energy Harvesting; Estimation and Identification; Fuel Cells/Energy Storage; Intelligent Transportation. Minneapolis, Minnesota, USA. October 12–14, 2016. V001T07A005. ASME. https://doi.org/10.1115/DSCC2016-9893
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