A linear algorithm for incremental digital display of circular arcs
Communications of the ACM
Integration, Coordination and Control of Multi-Sensor Robot Systems
Integration, Coordination and Control of Multi-Sensor Robot Systems
Merging Gaussian Distributions for Object Localization in Multi-robot Systems
ISER '00 Experimental Robotics VII
Cooperative Probabilistic State Estimation for Vision-Based Autonomous Soccer Robots
RoboCup 2001: Robot Soccer World Cup V
From Multiple Images to a Consistent View
RoboCup 2000: Robot Soccer World Cup IV
A Multi-Sensor Object Localization System
VMV '01 Proceedings of the Vision Modeling and Visualization Conference 2001
Information combination operators for data fusion: a comparative review with classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Multirobot object localization: a fuzzy fusion approach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy uncertainty modeling for grid based localization of mobile robots
International Journal of Approximate Reasoning
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Cooperative localization of objects is an important challenge in multi-robot systems. We propose a new approach to this problem where we see each robot as an expert which shares unreliable information about object locations. The information provided by different robots is then combined using fuzzy logic techniques, in order to reach a consensus between the robots. This contrasts with most current probabilistic techniques, which average information from different robots in order to obtain a tradeoff, and can thus incur well-known problems when information is unreliable. In addition, our approach does not assume that the robots have accurate self-localization. Instead, uncertainty in the pose of the sensing robot is propagated to object position estimates. We present experimental results obtained on a team of Sony AIBO robots, where we share information about the location of the ball in the RoboCup domain.