Haptic interfaces for compensating dynamics of rescue walking robots

This paper presents a Neural Network approach to compensate dynamic terms, friction force in particular, of a rescue walking robot used in haptic interfaces. The impedance control through dynamic compensation of the friction force is studied, followed by the implementation of neural intelligent networks in the feed-forward loop in order to eliminate the corresponding terms in the dynamics, friction force in particular. The friction force model is analyzed using a general compensation method after which a trained Multi-Layer Neural Network is introduced in order to obtain an accurate friction model so that the movement of the walking robot feels free and unconstraint. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).