Optimal exploration in unknown environments

This paper presents an algorithm that optimally explores an unknown environment with regions of varying degrees of importance. The algorithm, termed Ergodic Environmental Exploration (E³), is a finite receding horizon optimal control algorithm that minimizes control effort and the difference between the time average behavior of the system's trajectory and the distribution of the gain in information. The novelty of the E³ algorithm is the gain in information distribution used in the exploration trajectory optimization. The gain in information distribution uses an estimate of the information distribution and the confidence value on that estimate. Successful experiments have been conducted using E³ on a real mobile robot to explore an unknown 2-dimensional area. Results of these experiments are discussed and displayed with figures and a movie.