Surface identification using simple contact dynamics for mobile robots

This paper describes an approach to surface identification in the context of mobile robotics, applicable to supervised and unsupervised learning. The identification is based on analyzing the tip acceleration patterns induced in a metallic rod, dragged along a surface that is to be identified. Eight features in time and frequency domains are used for classification. Results show that for ten type of indoor and outdoor surfaces, reliable identification can be achieved (90.0 and 94.6 percent for a 1 and 4 seconds time-window, respectively), using a non-sophisticated classifier (artificial neural network). Demonstration is done on how such a sensor and a simple control strategy can be used to guide a blind robot, using a simulation and a real differential drive robot.

I. INTRODUCTION

This paper discusses a simple approach to terrain identification, based on the exploitation of contact dynamics. Surface sensing using a feeler can have several advantages for navigation. In the simplest case, the feeler can be used to detect anomalous surface conditions such as holes in the ground. More interestingly, it can be used to probe terrain properties. These properties, for example visco-elasticity or friction, might be challenging to measure accurately using vision or laser range-finders.