Control of robotic joints using principles from the equilibrium point hypothesis of animal motor control
Migliore, Shane Anthony
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Biological systems are able to perform complex movements with high energy-efficiency and, in general, can adapt to environmental changes more elegantly than traditionally engineered mechanical systems. The Equilibrium Point Hypothesis describes animal motor control as trajectories of equilibrium joint angle and joint stiffness. Traditional approaches to robot design are unable to implement this control scheme because they lack joint actuation methods that can control mechanical stiffness, and, in general, they are unable to take advantage of energy introduced into the system by the environment. In this paper, we describe the development and implementation of an FPGA-controlled, servo-actuated robotic joint that incorporates series-elastic actuation with specially developed nonlinear springs. We show that the joint's equilibrium angle and stiffness are independently controllable and that their independence is not lost in the presence of external joint torques. This approach to joint control emulates the behavior of antagonistic muscles, and thus produces a mechanical system that demonstrates biological similarity both in its observable output and in its method of control.