Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Multi-robot collaboration for robust exploration
Annals of Mathematics and Artificial Intelligence
An Experimental Study of a Cooperative Positioning System
Autonomous Robots
A Probabilistic Approach to Collaborative Multi-Robot Localization
Autonomous Robots
Using Situated Communication in Distributed Autonomous Mobile Robotics
SCAI '01 Proceedings of the Seventh Scandinavian Conference on Artificial Intelligence
Distributed Cooperative Outdoor Multirobot Localization and Mapping
Autonomous Robots
Evolution of Signaling in a Multi-Robot System: Categorization and Communication
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Experimental Comparison of Extended Kalman and Particle Filter in Mobile Robotic Localization
CERMA '09 Proceedings of the 2009 Electronics, Robotics and Automotive Mechanics Conference (cerma 2009)
Collective decision-making based on social odometry
Neural Computing and Applications
Evaluating the effect of robot group size on relative localisation precision
TAROS'11 Proceedings of the 12th Annual conference on Towards autonomous robotic systems
Performance analysis of multirobot Cooperative localization
IEEE Transactions on Robotics
Robotics and Autonomous Systems
Information Sciences: an International Journal
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When looking at unmanned ground vehicles (UGVs), nowadays multi-robot systems are considered an adequate choice for a growing number of tasks. Many problems, which are sufficiently solved for single vehicles, have to be revised when transferred into the multi-robot domain. This paper deals with cooperative position estimation in terms of pure relative localisation, which is based only on mutual observations among the robots. In this case, the localisation is independent of any characteristics of the surrounding environment. Thus, it is an important and interesting question how the number of robots influences the quality of the resulting localisation. After a short description of the underlying localisation approach, the design of the experiments is discussed and justified in detail. Special care is taken to assess possibly influencing parameters and their effects on the collected data. The authors' expectation that more robots should improve the position estimation is motivated. Unfortunately, the experimental results only partially match the expectation. A detailed analysis of the collected data was carried out to provide reasons for this.