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Author Rosencrantz, Matt ♦ Gordon, Geoffrey ♦ Thrun, Sebastian
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Distributed Particle Filter ♦ Sensor Fusion ♦ Platform Exchange Information ♦ Scalable Bayesian Technique ♦ Centralized Architecture ♦ Distributed Surveillance Scenario ♦ Laser Tag ♦ Physical Robot ♦ Decentralized State Estimation ♦ Information Flow ♦ Unprecedented Scaling Capability ♦ Enormous Communication Overhead ♦ Interactive Communication Protocol ♦ Dynamic Environment ♦ Distributed System ♦ Multiple Platform ♦ Severe Scaling Limitation ♦ Large Team ♦ Robotic System
Abstract This paper presents a scalable Bayesian technique for decentralized state estimation from multiple platforms in dynamic environments. As has long been recognized, centralized architectures impose severe scaling limitations for distributed systems due to the enormous communication overheads. We propose a strictly decentralized approach in which only nearby platforms exchange information. They do so through an interactive communication protocol aimed at maximizing information flow. Our approach is evaluated in the context of a distributed surveillance scenario that arises in a robotic system for playing the game of laser tag. Our results, both from simulation and using physical robots, illustrate an unprecedented scaling capability to large teams of vehicles.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2003-01-01