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.
Comments: 7 Pages.
[v1] 2018-03-22 09:28:01
Unique-IP document downloads: 5 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.