Cooperative stochastic position estimation of multiple mobile robots equipped with omnidirectional cameras

This paper proposes the cooperative position estimation of a group of mobile robots, which performs disaster relief tasks in a wide area. When searching the wide area, it becomes important to know a robot´s position correctly. However, each mobile robot is impossible to know its own position correctly. Therefor each mobile robot estimates its position from the data of sensor equipped on it. Generally, the sensor data is incorrect since there is sensor noise, etc. This research considers two types of the sensor data error from omnidirectional camera. One is the error of white noise of the image captured by omnidirectional camera and so on. Another is the error of a position and posture between two omnidirectional cameras. To solve the error of latter case, we proposed a self-position estimation algorithm for multiple mobile robots using two omnidirectional cameras and an accelerometer. On the other hand, to solve the error of the former case, this paper proposed an algorithm of cooperative position estimation for multiple mobile robots. In this algorithm, each mobile robot uses two omnidirectional cameras to observe the surrounding mobile robot and get the relative position between mobile robots. Each mobile robot estimates its position with only measurement data of each other mobile robots. The algorithm is based on a Bayesian filtering. Simulations of the proposed cooperative position estimation algorithm for multiple mobile robots are performed. The results show that position estimation is possible by using only measurement value from each other robot.