A control algorithm for automated pursuit

This paper presents an algorithm for controlling a nonholonomic automated vehicle following a moving target using only range and azimuth information. The automated vehicle is controlled dynamically by torque and steering rate -second and first order processes respectively. Obstacle avoidance is incorporated via a harmonic potential model of the world. Errors in range and azimuth are considered, as is data acquisition latency. A bicycle model simulation is presented. Position errors are important, but latency is not. Obstacles show a tendency to destabilize the current version of the algorithm.