2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2017
DOI: 10.1109/iros.2017.8206530
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Self-reconfiguration of modular underwater robots using an energy heuristic

Abstract: Abstract-This paper investigates self-reconfiguration of a modular robotic system, which consists of a cluster of modular vehicles that can attach to each other by a connection mechanism. Thereby, they can form a desired morphology to meet task specific requirements. Reconfiguration can be needed due to limitations from dimensions of passable corridors for an underwater maintenance task, for supplemental instrumentation that is available on a particular robot, or as remedial action if one robot in a cluster su… Show more

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Cited by 19 publications
(10 citation statements)
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References 23 publications
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“…Christensen et al (), Furno, Blanke, Galeazzi, and Christensen (), Furno, Blanke, Galeazzi, and Christensen ()…”
Section: Amv Fleetsmentioning
confidence: 99%
“…Christensen et al (), Furno, Blanke, Galeazzi, and Christensen (), Furno, Blanke, Galeazzi, and Christensen ()…”
Section: Amv Fleetsmentioning
confidence: 99%
“…The REMORA project represents collaborative underwater robots designed for inspection and repair of underwater foundations and rigs [50]. The modular design of these robots result in a collaboration, wherein other REMORA robots are able to merge into a larger device through a connection mechanism to overcome environmental challenges that would overwhelm single platforms [51]. This unique function results in increased resilience via shared system awareness and fault recovery.…”
Section: ) Underwater Roboticsmentioning
confidence: 99%
“…The REMORA project [39] examines the use of aquatic modular robots for the inspection and maintenance of off-shore structures, such as oil platforms. The robots can move underwater in 3-D. Furno et al [28] present a hardware prototype of the system and perform experiments in which three robots reconfigure from an "I" shape to an "L" shape.…”
Section: A Self-propelled Modular Systemsmentioning
confidence: 99%