Effective Task Allocation by Enhancing Divisional Cooperation in Multi-Agent Continuous Patrolling Tasks

Sugiyama, Ayumi; Sea, Vourchteang; Sugawara, Toshiharu

doi:10.1109/ictai.2016.0016

Cited by 9 publications

(4 citation statements)

References 17 publications

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“…Sea et al [15,16] presented a decentralized partitioning method for cleaning tasks of multiple agents under the grid environment. Sugiyama et al [17] designed different visit frequencies for all purposes in the patrolling area and applied divisional cooperation to achieve the patrol tasks. Yasuyuki et al [18] applied reinforcement learning based on discrete patrolling areas to perform security patrol tasks.…”

Section: Related Workmentioning

confidence: 99%

“…PSO uses a fitness function to evaluate the quality of particles (line 16). The global optimal position of the particle swarm is updated iteratively, which is iterated until the maximum number of iterations (lines [17][18]. must return to the base station and replenish fuel, and then continue to visit the area to be visited.…”

Section: Patrolling Path Planning Algorithm Based On Improved Psomentioning

confidence: 99%

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Hybrid Partition-Based Patrolling Scheme for Maritime Area Patrol with Multiple Cooperative Unmanned Surface Vehicles

Xie

Zhou

Luo

et al. 2020

JMSE

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Multi-robot cooperative patrolling systems have been extensively employed in the civilian and military fields, including monitoring forest fires, marine search-and-rescue, and area patrol. Multi-robot area patrol problems refer to the activity that a team of robots works cooperatively and regularly to visit the key targets in the given area for security. Following consideration of the low cost and high safety of unmanned surface vehicles (USV), a team of USVs is organized to perform area patrol in a sophisticated maritime environment. In this paper, we establish a mathematical model considering the characteristics of the cooperative patrol task and the limited conditions of USVs. A hybrid partition-based patrolling scheme is proposed for a multi-USV system to visit targets with different importance levels in a maritime area. Firstly, a centralized area partition algorithm is utilized to partition the patrolling area according to the number of USVs. Secondly, a distributed path planning algorithm is applied to planning the patrolling path for each USV to visit the targets in a maritime environment to minimize the length of the patrolling path for the USV team. Finally, comparative experiments between the proposed scheme and other methods are carried out to validate the performance of the hybrid partition-based patrolling scheme. Simulation results and experimental analysis show the efficiency of the proposed hybrid partition-based patrolling scheme compared to several previous patrolling algorithms.

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Section: Related Workmentioning

confidence: 99%

Section: Patrolling Path Planning Algorithm Based On Improved Psomentioning

confidence: 99%

Hybrid Partition-Based Patrolling Scheme for Maritime Area Patrol with Multiple Cooperative Unmanned Surface Vehicles

Xie

Zhou

Luo

et al. 2020

JMSE

View full text Add to dashboard Cite

show abstract

“…In 2015 Jeyhun and Murat [2] proposed a hybrid K-means clustering algorithm that optimizes the initial center of mass using a hybrid intelligent algorithm to achieve better partitioning, but does not consider the variability in the frequency of visits to each location within the search area. In 2016, Sugiyama et al [3] discussed the problem of continuous collaborative patrol search for access points with different frequencies, but the method did not consider the problem of region delimitation. In 2017, Sea et al [4,5] proposed a balanced load region partitioning method for continuous collaborative tasks in the field of robotics, which is an important reference for the study of multi-USV task assignment problems.…”

Section: Introductionmentioning

confidence: 99%

Path planning and search effectiveness of USV based on underwater target scattering model

Niu

Zhang

et al. 2023

J. Phys.: Conf. Ser.

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A multi-USV optimal path planning algorithm based on underwater target scattering model is proposed for the difficult problem of combining path planning and underwater target sonar search for Unmanned Surface Vehicle (USV). The algorithm is based on the characteristics of multi-USV collaborative search problem, and then constructs the partition search model with improved k-means algorithm and the sub-region path planning algorithm model with improved particle swarm algorithm (PSO). And in order to be closer to the needs of the actual scenario, the target submarine dispersion model and the dipped sonar search model are constructed. Combined with the area partitioning algorithm module and the path planning algorithm module, it is applied to the effectiveness calculation of searching for submarine targets. Through simulation and comparison experiments, we verified the effectiveness and superiority of the proposed path planning algorithm in this paper.

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“…The first type involved a larger number of robots performing less demanding tasks such as swarm systems. The second involved a moderate number of robots (10-30) (Sugiyama et al 2016;Cheng et al 2016). The third included a low number of robots performing very complex tasks (Khalfi et al 2016;Wang et al 2016;Hongli et al 2016).…”

Section: Systematic Reviewmentioning

confidence: 99%

Solving the task variant allocation problem in distributed robotics

et al. 2018

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We consider the problem of assigning software processes (or tasks) to hardware processors in distributed robotics environments. We introduce the notion of a task variant, which supports the adaptation of software to specific hardware configurations. Task variants facilitate the trade-off of functional quality versus the requisite capacity and type of target execution processors. We formalise the problem of assigning task variants to processors as a mathematical model that incorporates typical constraints found in robotics applications; the model is a constrained form of a multi-objective, multi-dimensional, multiple-choice knapsack problem. We propose and evaluate three different solution methods to the problem: constraint programming, a constructive greedy heuristic and a local search metaheuristic. Furthermore, we demonstrate the use of task variants in a real instance of a distributed interactive multi-agent navigation system, showing that our best solution method (constraint programming) improves the system's quality of service, as compared to the local search metaheuristic, the greedy heuristic and a randomised solution, by an average of 16, 31 and 56% respectively.

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Effective Task Allocation by Enhancing Divisional Cooperation in Multi-Agent Continuous Patrolling Tasks

Cited by 9 publications

References 17 publications

Hybrid Partition-Based Patrolling Scheme for Maritime Area Patrol with Multiple Cooperative Unmanned Surface Vehicles

Hybrid Partition-Based Patrolling Scheme for Maritime Area Patrol with Multiple Cooperative Unmanned Surface Vehicles

Path planning and search effectiveness of USV based on underwater target scattering model

Solving the task variant allocation problem in distributed robotics

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