Servo load analysis for the classification of surface of locomotion in a modular snake-like robot

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Resumen

This paper shows the possibility of classifying the surface of locomotion of a modular snake-like robot only from torque and current sensors in the servo-motors. Locomotion in modular snake-like robots is made from gaits that involve the entire body structure, in this particular work we use a modular snake-like robot consisting of 16 modules located 90 degrees rotated one with respect to the previous, this robot is built from Dynamixel AX-12 servos, these servos provide load information based on torque and power consumption. This article presents an analysis from two classifiers, supervised and unsupervised for load temporary data in each of the 16 modules, for three different gaits used in the robot, linear progression, side winding and lateral rolling to make an identification of the characteristics of the surface on which the robot is moving, all without the need for other external sensors. The reported results are obtained by applying two classification techniques, the first supervised (SVM) and the second unsupervised (K-means). Is concluded that it is possible to make a classification between surfaces, knowing previously the selected gait, reaching even to 100% accurancy for certain gaits.

Idioma originalInglés
Título de la publicación alojadaSTSIVA 2012 - 17th Symposium of Image, Signal Processing, and Artificial Vision
Páginas13-18
Número de páginas6
DOI
EstadoPublicada - 2012
Evento17th Symposium of Image, Signal Processing, and Artificial Vision, STSIVA 2012 - Medellin, Colombia
Duración: 12 sep. 201214 sep. 2012

Serie de la publicación

NombreSTSIVA 2012 - 17th Symposium of Image, Signal Processing, and Artificial Vision

Conferencia

Conferencia17th Symposium of Image, Signal Processing, and Artificial Vision, STSIVA 2012
País/TerritorioColombia
CiudadMedellin
Período12/09/1214/09/12

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