Knowledge-based expert system using a set of rules to assist a tele-operated mobile robot

Abstract

This paper firstly reviews five artificial intelligence tools that might be useful in helping tele-operators to drive mobile robots: knowledge-based systems (including rule based systems and case-based reasoning), automatic knowledge acquisition, fuzzy logic, neural networks and genetic algorithms. Rule-based systems were selected to provide real time support to tele-operators with their steering because the systems allow tele-operators to be included in the driving as much as possible and to reach their target destination, while helping when needed to avoid an obstacle. A bearing to an end-point is added as an input with an obstacle avoidance sensor system and the usual inputs from a joystick. A recommended direction is combined with the angle and position of a joystick and the rule-based scheme generates a recommended angle to rotate the mobile robot. That recommended angle is then blended with the user input to assist tele-operators with steering their robots in the direction of their destinations.