首页|Researchers from University of Ottawa Report Recent Findings in Robotics and Aut omation (Stability of Human Balance During Quiet Stance With Physiological and E xoskeleton Time Delays)

Researchers from University of Ottawa Report Recent Findings in Robotics and Aut omation (Stability of Human Balance During Quiet Stance With Physiological and E xoskeleton Time Delays)

扫码查看
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Robotics - Robotics a nd Automation have been presented. According to news reporting originating from Ottawa, Canada, by NewsRx correspondents, research stated, "Human balance with e xoskeleton assistance is studied using an inverted pendulum model, considering t ime delays in the muscle reflexes and the exoskeleton controller. The model incl udes two motors at the ankle joint whose maximum torques depend on the joint ang le and angular velocity, reflecting the combined moment-generating capacity of a ll plantarflexor and dorsiflexor muscles." Financial support for this research came from CGIAR. Our news editors obtained a quote from the research from the University of Ottaw a, "These ‘musclelike' motors obey a proportional-derivative (PD) reflex contro l law where the angle and angular velocity of the ankle joint are subject to fee dback delays. The stability of this system is analyzed using Galerkin projection to convert the governing neutral delay differential equation into a system of f irst-order ordinary differential equations (ODEs) and computing the eigenvalues of the ODE system. The stability analysis is then repeated with exoskeleton torq ues included at the ankle joint. The exoskeleton torques are assumed to obey a P D control law as well but with a unique state feedback delay. Stability charts r eveal that the area of the stability region always increases as the exoskeleton delay decreases, but the area may decrease as the physiological delay decreases. "

OttawaCanadaNorth and Central Americ aRobotics and AutomationRoboticsUniversity of Ottawa

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Mar.8)