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Fox, Dieter; Burgard, Wolfram; Kruppa, Hannes; Thrun, Sebastian

doi:10.1023/a:1008937911390

Cited by 523 publications

(45 citation statements)

References 43 publications

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“…[Burgard et al, 2011], [Guanghui et al, 2007]), or can take advantage of the perspectives of multiple agents inhabiting the same environment. Approaches in the latter category, such as those of Fox et al [2000] and Martinelli et al [2005], use mutual observation between robots to allow robots in close proximity to share data in order to aid in their respective localization efforts. The encounter provides a common reference point which both robots use to establish a common localization.…”

Section: Localization and Shared Coordinate Systemsmentioning

confidence: 99%

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Dynamic heterogeneous team formation for robotic urban search and rescue

Gunn

Anderson

2015

Journal of Computer and System Sciences

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Using teams of robots to complete a task provides a number of advantages over the use of a single robot. Multiple robots are able to complete tasks faster, and provide redundancy in case of equipment failure or loss. Teams of robots with different capabilities and physiologies are beneficial because they allow a team to provide a high level of overall functionality while striking a balance between the cost and complexity of the robots. Previous work tends to focus on the use of pre-formed teams of robots, with little attention to the formation and maintenance of the team itself. An environment such as a disaster zone presents numerous challenges to robotic operation, and it can be expected that the nature of a team will change due to, for example, malfunctions and the introduction of replacement equipment. I developed a framework to support the maintenance of teams of heterogeneous robots operating in complex and dynamic environments such as disaster zones. Given an established team, my work also facilitates the discovery of work to be done during the team's mission and its subsequent assignment to members of the team in a distributed fashion. I evaluated my framework through the development of an example implementation where robots perform exploration in order to locate victims in a simulated disaster environment.ii

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Section: Localization and Shared Coordinate Systemsmentioning

confidence: 99%

“…An implementation in a USAR test bed could, for example, use a probabilistic approach (e.g. [Fox et al, 2000] or [Martinelli et al, 2005]). …”

Section: Localization and Coordinate Systemsmentioning

confidence: 99%

Dynamic heterogeneous team formation for robotic urban search and rescue

Gunn

Anderson

2015

Journal of Computer and System Sciences

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“…Designing and controlling robot assemblies to achieve specific collective goals has drawn considerable interest in recent years [1,2,3,4]. An individual agent may be programmed to be fully autonomous and independent, but because of physical and resource constraints, its abilities may be limited.…”

Section: Introductionmentioning

confidence: 99%

Pattern Formation Stability and Collapse in 2D Driven Particle Systems

D’Orsogna¹,

Chuang

Bertozzi³

et al.

Device Applications of Nonlinear Dynamics

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Interacting, multi-robot systems show increasing promise for advances in exploration and defense applications. Here, we model a non-linear system of self-propelled individuals interacting via a pairwise attractive and repulsive potential. Depending on the interaction parameters, the agents may disperse, accumulate into self-organizing structures such as flocks and vortices, or collapse onto themselves. Borrowing tools from Statistical Mechanics, we discuss the connections between the H-stable nature of the interaction potential and resulting aggregating patterns and asymptotic behaviors.

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“…This choice is justified by the fact that the collaboration of several simple and not expensive robots, proves to be faster and more efficient than using a large complex robot [6]. Furthermore, it has been proved that as the different perceptions resources are shared and merged, the reliability of information is increased in addition to the accuracy of the model representing the covered areas [7]. On the other hand, the failure or the loss of one or more robots does not necessarily mean the interruption of the exploration task.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of different frontier-based multi-robot exploration strategies

Benkrid

Benallègue²,

Achour

2016

MATEC Web of Conferences

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Abstract. In this paper, we focus on the problem of exploring an unknown environment by a team of mobile robots. The main objective is to compare four different coordination strategies based on frontier concept (boundaries between unexplored and explored open areas) and analyze their performance in term of assignment quality, overall exploration time and computational complexity. In order to provide a suitable qualitative study we used three optimization criteria. Each strategy has been implemented and tested extensively in computerized simulation.

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Cited by 523 publications

References 43 publications

Dynamic heterogeneous team formation for robotic urban search and rescue

Dynamic heterogeneous team formation for robotic urban search and rescue

Pattern Formation Stability and Collapse in 2D Driven Particle Systems

Evaluation of different frontier-based multi-robot exploration strategies

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