Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems 2009
DOI: 10.1145/1865909.1865932
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Evaluating the RoboCup 2009 Virtual Robot Rescue Competition

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Cited by 6 publications
(4 citation statements)
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“…A virtual competition for rescue offers larger, more complex environments and stresses collaborative planning of teams of robots [17]. Teams are required to address elemental tasks that include the autonomous distribution of up to eight robots to form communication repeater networks, autonomous multi-vehicle mapping, and multi-vehicle tele-operation.…”
Section: Spectrum Of Competitionsmentioning
confidence: 99%
“…A virtual competition for rescue offers larger, more complex environments and stresses collaborative planning of teams of robots [17]. Teams are required to address elemental tasks that include the autonomous distribution of up to eight robots to form communication repeater networks, autonomous multi-vehicle mapping, and multi-vehicle tele-operation.…”
Section: Spectrum Of Competitionsmentioning
confidence: 99%
“…This study is meant to include the influence of smoke to measurements of the laser range finders. Laser range finders are used by all teams in the competition for localization and mapping purposes [8]. The findings in this paper are also relevant outside the competition; the explicit model is complete enough to be implemented and contains details needed any study about the relationship between laser range finders and smoke.…”
Section: Introductionmentioning
confidence: 99%
“…Multi-agent systems have garnered much attention of late with recent advances in computing and robotics (from [12] to [2]), wherein a single task is achieved by several agents working cooperatively in a distributed fashion [42]. Example applications which could be achieved using this multi-agent platform include robot rescue [5], intruder detection [24] and mobile ad-hoc wireless network research [40]. Historically, the problem of localisation for mobile robots has been addressed in one of two ways: using either global (external) information or local (internal) information to achieve absolute or relative localisation of the robot.…”
Section: Introductionmentioning
confidence: 99%