Motion Planning of Networked Multi-Vehicle System with Hybrid Measurement Model

This paper presents a new motion planning method of a multi-vehicle system in which vehicles can mutually measure the location of other vehicles when distances between vehicles are close. The mutual measurement method reduces uncertainty of location estimation by providing additional information. We propose a motion planning method based on the existence of maximal distance of mutual measurement. We formulate a multi-vehicle system with some disturbance and a new hybrid measurement model. The new model is a hybrid of maximal distance of mutual measurement and Kalman filter. The receding horizon control method is shown to be applicable to the new hybrid measurement model. We demonstrate the validity of our new hybrid measurement model in computer simulation.