Theory and application of multi-robot service-oriented architecture

Cai, Yi; Tang, Zhenmin; Ding, Y. X.; Qian, Bin

doi:10.1109/jas.2016.7373758

Cited by 23 publications

(8 citation statements)

References 13 publications

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“…Associated with the application of the FIS, the purpose is to approximate the system uncertainties in (8) so that the approximate values are definitely selected as the FIS outputs, i.e., b =d ik (x ik ,ẋ ik , t). Moreover, the system uncertainties in (8) are functions of x ik andẋ ik so that l ik , ψ ik ,l ik andψ ik are picked up as the FIS inputs, i.e., a =…”

Section: Design Of Fuzzy Compensatormentioning

confidence: 99%

“…Up to now, various formation schemes have been presented and carried out. They can roughly be classified as behavior-based methods, virtual structure techniques and leader-follower schemes [4,8]. Among them, the leaderfollower approaches have become the most popular ones because the idea is simple enough to permit complete analyses and experiments, but the internal formation stability can be theoretically guaranteed [9,10].…”

Section: Introductionmentioning

confidence: 99%

“…The basic idea of the leader-follower formations [8,11] is that one robot in a multi-robot system is selected as leader and the other robots are called followers. The leader is responsible for guiding the formation and the followers are required to track the leader in the desired distance l and the desired relative angle ψ.…”

Section: Introductionmentioning

confidence: 99%

“…Accordingly, there are two kinds of control frameworks, i.e., l −l and l −ψ. Considering the leader-follower approaches, a characteristic is that the formation problem of the multi-robot system is transformed into the independent trajectory tracking problem of each follower robot [4,[8][9][10][11]. Although the basic idea is in dispute over its 'single point of failure', such characteristic benefits the formation problem a lot.…”

Section: Introductionmentioning

confidence: 99%

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Robust Multi-robot Formations via Sliding Mode Controller and Fuzzy Compensator

Qian

2016

Automatika

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Original scientific paper To form up a multiple-robot system, a robust adaptive control scheme is addressed. The control scheme is based on the methodology of sliding mode control (SMC). The formation system is leader-follower-based, whose dynamics are subject to uncertainties. A fuzzy compensator is adopted to approximate the uncertainties. To attenuate the approximation error, a robust adaptive law of the fuzzy compensator is introduced. In the sense of Lyapunov, not only such a control scheme can asymptotically stabilize the whole formation system, but also the convergence of the approximation error can be guaranteed. Compared with the sole sliding mode controller without compensator, some numerical simulations verify the feasibility and effectiveness of the control scheme for the multiple-robot system in the presence of uncertainties.

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Section: Design Of Fuzzy Compensatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust Multi-robot Formations via Sliding Mode Controller and Fuzzy Compensator

Qian

2016

Automatika

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“…The ambient assisted living service system based on scale‐invariant feature transform (SIFT) algorithm that proposed in [8] can locate the objects who have service demands for elderly and disabled. A service architecture is proposed to solve the problem of heterogeneity in multi‐robot cooperation [9]. A mobile robot is able to perceive the surrounding environment and interact with people in [10].…”

Section: Introductionmentioning

confidence: 99%

Proposal of initiative service model for service robot

Hao

Cao

et al. 2017

CAAI Transactions on Intelligence Technology

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Service robots are becoming a part of today's life. To realise friendly human-robot interaction, an initiative service model for service robot is proposed, which is composed of three layers, i.e. information acquisition layer, in which communication information and environmental information are collected by sensors; decision layer, in which personal intention and emotional states are obtained by multi-modal emotion recognition and intention understanding, and users' demands are obtained by demand analysis model; initiative service execution layer, in which the task execution and emotion adaption of robot are carried out. Initiative service can sense motive of people, by which a humanised and real-time service could be realised. Drinking service experiments are performed, including passive service and initiative service of robots. Experimental results show that the drinking time of passive service lags behind the initiative service 30 min on average, and the initiative service renders drinking service 2 times more than passive service on average, besides, the water quantity provided by initiative service is more reasonable, which demonstrates the feasibility of the proposal. In prospect, initiative service model could be applied to many occasions in people's daily life, e.g. family service, caring for the elderly, and medical rehabilitation.

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SOAP-Based Web Service for Localization of Multi-robot System in Cloud

Hayet

Knani

2018

Advances in Intelligent Systems and Computing

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Theory and application of multi-robot service-oriented architecture

Cited by 23 publications

References 13 publications

Robust Multi-robot Formations via Sliding Mode Controller and Fuzzy Compensator

Robust Multi-robot Formations via Sliding Mode Controller and Fuzzy Compensator

Proposal of initiative service model for service robot

SOAP-Based Web Service for Localization of Multi-robot System in Cloud

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