Parameter estimation for multi-agent path finding with stochastic travel times

Abstract

In the delivery services in office buildings using automated robots, pedestrians and a wide variety of robots coexist, and the robots travel along the aisles while avoiding these obstacles, so the time required to cross an aisle is not constant, and information on the distribution of travel time is often insufficient or inaccurate. This study proposes a method for estimating the parameters of the probability distribution of travel time using Bayesian inference for multi-agent path finding problems where the travel time varies stochastically, and the probability distribution is not given a priori but must be estimated based on information obtained during operation. Through simulations, we compare the performance of our method with existing methods.