Coordination for dynamic weighted task allocation in disaster environments with time, space and communication constraints

Su, Xing; Zhang, Minjie; Bai, Quan

doi:10.1016/j.jpdc.2016.06.010

Cited by 18 publications

(13 citation statements)

References 21 publications

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“…The [ST-MR] configuration is addressed by very few researchers 20,21 and the use of conventional optimisation methods to solve problems of [ST-MR] setup involves many variables, and hence it is computationally intensive to find a solution. Moreover, the effect of precedence constraints in [ST-MR] problems and objectives related to robots such as a number of robots utilised, waiting time and idle times of robots were given least importance when compared to task-related goals.…”

Section: Related Workmentioning

confidence: 99%

Multi-objective Optimisation of Multi-robot Task Allocation with Precedence Constraints

et al. 2018

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Efficacy of the multi-robot systems depends on proper sequencing and optimal allocation of robots to the tasks. Focuses on deciding the optimal allocation of set-of-robots to a set-of-tasks with precedence constraints considering multiple objectives. Taguchi’s design of experiments based parameter tuned genetic algorithm (GA) is developed for generalised task allocation of single-task robots to multi-robot tasks. The developed methodology is tested for 16 scenarios by varying the number of robots and number of tasks. The scenarios were tested in a simulated environment with a maximum of 20 robots and 40 multi-robot foraging tasks. The tradeoff between performance measures for the allocations obtained through GA for different task levels was used to decide the optimal number of robots. It is evident that the tradeoffs occur at 20 per cent of performance measures and the optimal number of robot varies between 10 and 15 for almost all the task levels. This method shows good convergence and found that the precedence constraints affect the optimal number of robots required for a particular task level.

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Section: Related Workmentioning

confidence: 99%

Multi-objective Optimisation of Multi-robot Task Allocation with Precedence Constraints

et al. 2018

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“…The coefficient λ j needs to be tuned when applied in different cases. The bid price p ij is defined in Equation (9).…”

Section: The Bidding Strategy Of Biddersmentioning

confidence: 99%

“…Many approaches for the task allocation problem have been proposed, such as contract net protocol [8,9], intelligent algorithm-based approaches [10][11][12][13] and auction-based approaches [14][15][16], etc.…”

Section: Introductionmentioning

confidence: 99%

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Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism

et al. 2017

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Abstract:In this paper, we optimize the search and rescue (SAR) in disaster relief through agent-based simulation. We simulate rescue teams' search behaviors with the improved Truncated Lévy walks. Then we propose a cooperative rescue plan based on a distributed auction mechanism, and illustrate it with the case of landslide disaster relief. The simulation is conducted in three scenarios, including "fatal", "serious" and "normal". Compared with the non-cooperative rescue plan, the proposed rescue plan in this paper would increase victims' relative survival probability by 7-15%, increase the ratio of survivors getting rescued by 5.3-12.9%, and decrease the average elapsed time for one site getting rescued by 16.6-21.6%. The robustness analysis shows that search radius can affect the rescue efficiency significantly, while the scope of cooperation cannot. The sensitivity analysis shows that the two parameters, the time limit for completing rescue operations in one buried site and the maximum turning angle for next step, both have a great influence on rescue efficiency, and there exists optimal value for both of them in view of rescue efficiency.

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“…Another work that considers how to allocate roles or tasks on a team in a decentralized fashion is that of Xing Su et al [122]. The authors explore ad hoc teamwork in disaster response scenarios.…”

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confidence: 99%

Making Friends on the Fly: Advances in Ad Hoc Teamwork

Barrett¹

2015

Studies in Computational Intelligence

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Coordination for dynamic weighted task allocation in disaster environments with time, space and communication constraints

Cited by 18 publications

References 21 publications

Multi-objective Optimisation of Multi-robot Task Allocation with Precedence Constraints

Multi-objective Optimisation of Multi-robot Task Allocation with Precedence Constraints

Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism

Making Friends on the Fly: Advances in Ad Hoc Teamwork

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