Experiments in Consensus-based Distributed Cooperative Control of Multiple Mobile Robots

Cao, Yongcan; Ren, Wei; Sorensen, N.; Ballard, L.; Reiter, Alexander; Kennedy, James J.

doi:10.1109/icma.2007.4304006

Cited by 20 publications

(10 citation statements)

References 8 publications

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“…Recently, consensus problem of muti-agent systems has draw great attention for its broad potential applications in many areas such as cooperative control of vehicles[1,2] unmanned air vehicle formation [3][4][5]and flocking control [6,7]. It has been studies from different perspectives and many results have been got from different view points.…”

Section: Introductionmentioning

confidence: 99%

LQR_based consensus algorithms of muti-agent systems with a prescribed convergence speed

Liu

Zhou

Shi

et al. 2014

Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference

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This paper studies the consensus problem of muti-agent systems with identical linear invariant dynamics. Both with and without a leader situation are considered. The controllers are designed with static relative output feedback. The communication topology is assumed to be fixed and contain a directed spanning tree. An optimal design method is introduced to design feedback gain so that the system can converge to the consensus value with a prescribed convergence speed. I. INTRODUCTIONRecently, consensus problem of muti-agent systems has draw great attention for its broad potential applications in many areas such as cooperative control of vehicles[1,2] unmanned air vehicle formation [3][4][5]and flocking control [6,7]. It has been studies from different perspectives and many results have been got from different view points.In [8][9][10][11][12], consensus protocols were designed for first-order and second-order integral dynamics. High-order integral systems were studied in the articles [13][14][15]. The consensus problems of the general linear invariant dynamics which consider first-order and second-order integral dynamics as a special situation were studied in the recent works [1,[16][17][18][19][20][21][22]. In these papers, the consensus protocols were mostly designed with the neighbor's states or output as the feedback information. Different methods were used to design the consensus protocols. In [8,13,17,[23][24][25], the static state or output feedback was used to design the controllers. Dynamic feedback controllers were proposed in [23][24][25]. [17,26] proposed an observer-type consensus protocol with fixed communication topology which contains a directed spanning tree and the consensus regions were analyzed. In[17], tracking consensus problem was solved by optimal design method. Several protocols were proposed with static and dynamic state feedback. Unbounded synchronization regions were proposed. In [18], the consensusability of the multi-agent systems was studied with the communication topology contain a spanning tree. Necessary and sufficient conditions were proposed when the dynamics were both stabilizable and detectable. Many other control methods had been used to design the consensus protocols such as internal model principle [22,[27][28][29][30]. More consensus problems could be founded in the survey papers [11,31,32].

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Section: Introductionmentioning

confidence: 99%

LQR_based consensus algorithms of muti-agent systems with a prescribed convergence speed

Liu

Zhou

Shi

et al. 2014

Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference

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“…Examples of such missions include aerobiological sampling, persistent surveillance, formation control, distributed resource delivery, and target positioning [1,[3][4][5][6]. The tasks in these missions often require the agents to collaboratively sense, estimate, or reach agreement on global parameters/states, such as the states of the environment or shared variables related to task settings and assignments [7][8][9][10][11]. However, while low-cost agents have the potential to yield benefits such as scalability, cost-saving, and resiliency, these agents typically have limited onboard computation and communication resources.…”

Section: Introductionmentioning

confidence: 99%

“…Many distributed estimation algorithms use the notion of consensus to estimate the parameters/states of interest (e.g., [9][10][11][12][13][14][15][16]). In a typical consensus algorithm, an agent attempts to reach an agreement with its neighbors by performing a sequential update that brings its estimate closer to the states/parameters of (a subset of) all of its neighbors.…”

Section: Introductionmentioning

confidence: 99%

Efficient distributed sensing using adaptive censoring based inference

Chowdhary

How

2013

2013 American Control Conference

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In many distributed sensing applications it is likely that only a few agents will have valuable information at any given time. Since wireless communication between agents is resource-intensive, it is important to ensure that the communication effort is focused on communicating valuable information from informative agents. This paper presents communication-efficient distributed sensing algorithms that avoid network cluttering by having only agents with high Value of Information (VoI) broadcast their measurements to the network, while others censor themselves. A novel contribution of the presented distributed estimation algorithm is the use of an adaptively adjusted VoI threshold to determine which agents are informative. This adaptation enables the team to better balance between the communication cost incurred and the long-term accuracy of the estimation. Theoretical results are presented establishing the almost sure convergence of the communication cost and estimation error to zero for distributions in the exponential family. Furthermore, validation through numerical simulations and real datasets show that the new VoI-based algorithms can yield improved parameter estimates than those achieved by previously published hyperparameter consensus algorithms while incurring only a fraction of the communication cost.

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“…Equilibrium formations for nonholonomic systems have been an active area of research in recent times among many disciplines like biological sciences [1][2][3], computer graphics [4] and systems engineering [5][6][7][8]. One particular problem studied in this context has been the consensus seeking [9] or the state agreement problem [10] which deals with designing feedback controllers to make multiple agents converge to a common configuration in the global coordinates.…”

Section: Introductionmentioning

confidence: 99%