Evolving a lookup table based controller for robotic navigation

Abstract

This paper describes how lookup tables can be evolved to control the motion of a simulated two wheeled robot, whose functions are either to move towards a light source or avoid obstacles. The robot has two light sensors, six obstacle sensors and two DC motor drivers for the wheels. The lookup table controls the motion of the robot by changing the motor speeds dependent on the sensor values. For light following, the axes of the table are right and left light sensor levels, whilst for obstacle avoidance the axis is the bit combination of the six digital sensors. The parameters within both tables are left and right motor direction. The genetic algorithm using two point crossover with a mutation rate of three percent and tournament selection successfully evolved the lookup tables for both navigational tasks.