A multilayer perceptrons model for the stability of a bipedal robot
A neural network model is proposed as a means of controlling the dynamical equilibrium of a walking bipedal robot. As a criterion to determine the stability of such a robot in relation with the organization of the sensorimotor system, we have been making use of the ZMP (Zero Momentum Point). Simulations are used to check the convergence of the algorithm. In the generalization phase, it is shown that the neural network has the ability to stabilise the robot for motions which have not previously been learned. An extended model is proposed, which seeks to closely inspect the physiology of the cerebellar cortex.
neural networks dynamical equilibrium walking robots levenberg-marquardt's rules