An Experimental Study of a Cooperative Positioning System
Autonomous Robots
A Probabilistic Approach to Collaborative Multi-Robot Localization
Autonomous Robots
Distributed Cooperative Outdoor Multirobot Localization and Mapping
Autonomous Robots
Multi-robot Simultaneous Localization and Mapping using Particle Filters
International Journal of Robotics Research
Cooperative Visual Tracking in a Team of Autonomous Mobile Robots
RoboCup 2006: Robot Soccer World Cup X
Map-Based multiple model tracking of a moving object
RoboCup 2004
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In this paper we present an approach for a team of robots to cooperatively improve their self localization through collaboratively tracking a moving object. At first, we use a Bayes net model to describe the multi-robot self localization and object tracking problem. Then, by exploring the independencies between different parts of the joint state space of the complex system, we show how the posterior estimation of the joint state can be factorized and the moving object can serve as a bridgefor information exchange between the robots for realizing cooperative localization. Based on this, a particle filtering method for the joint state estimation problem is proposed. And, finally, in order to improve computational efficiency and achieve real-time implementation, we present a method for decoupling and distributing the joint state estimation onto different robots. The approach has been implemented on our four-legged AIBO robots and tested through different scenarios in RoboCup domain showing that the performance of localization can indeed be improved significantly.