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distributed task allocation for Multiple UAVs Based on Swarm Benefit Optimization

DRONES 2024年第12期8卷 766-766页

作者： Chen, Yiting Chen, Runfeng Huang, Yuchong Xiong, Zehao Li, Jie Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha 410073 Peoples R China

The auction mechanism stands as a pivotal distributed solution approach for addressing the task allocation problem in unmanned aerial vehicle (UAV) swarms, with its rapid solution capability well-suited to meet the real-time requirements of aerial mission planning for UAV swarms. Building upon the auction mechanism, this paper proposes a distributed task allocation method for multi-UAV grounded in swarm benefits optimization. The method introduces individual benefit variation to quantify the effect of a task on the benefit of a single UAV, thereby enabling direct optimization of swarm benefit through these individual benefit variations. Within the formulated individual benefit calculation, both the spatial distance between tasks and UAVs and the initial task value along with its temporal decay are taken into account, ensuring a thorough and accurate assessment. Additionally, the method incorporates real-time updates of individual benefits for each UAV, reflecting the dynamic state of task benefit fluctuations within the swarm. Monte Carlo simulation experiments demonstrate that, for a swarm size of 16 UAVs and 80 tasks, the proposed method achieves an average swarm benefit improvement of approximately 2% and 4% over the Consensus-Based Bundle Algorithm (CBBA) and Performance Impact (PI) methods, respectively, thus validating its effectiveness.

关键词： distributed task allocation multiple UAVs swarm benefits optimization auction mechanism

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An Agent-Based Planning Method for distributed task allocation 13th

An Agent-Based Planning Method for Distributed Task Allocati...

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13th International Conference on Software Technologies (ICSOFT)

作者： Ben Noureddine, Dhouha Gharbi, Atef Ben Ahmed, Samir Univ Carthage INSAT Natl Inst Appl Sci & Technol LISI Tunis Tunisia Univ El Manar FST Tunis Tunisia

ISBN: (纸本)9783030291570;9783030291563

In multi-agent systems, agents should socially cooperate with their neighboring agents in order to solve task allocation problem in open and dynamic network environments. This paper proposes an agent-based architecture to handle different tasks;in particular, we focus on planning and distributed task allocation. In the proposed approach, each agent uses the fuzzy logic technique to select the alternative plans. We also propose an efficient task allocation algorithm that takes into consideration agent architectures and allows neighboring agents to help to perform a task as well as the indirectly related agents in the system. We illustrate our line of thought with a Benchmark Production System used as a running example in order to explain better our contribution. A set of experiments was conducted to demonstrate the efficiency of our planning approach and the performance of our distributed task allocation method.

关键词： Multi-agent system Software architecture distributed task allocation Planning Fuzzy logic

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Effect of Alternative distributed task allocation Strategy Based on Local Observations in Contract Net Protocol

Effect of Alternative Distributed Task Allocation Strategy B...

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13th International Conference on Principles and Practice of Multi-Agent Systems

作者： Sugawara, Toshiharu Fukuda, Kensuke Hirotsu, Toshio Kurihara, Satoshi Waseda Univ Dept Comp Sci & Engn Tokyo 1698555 Japan Natl Inst Informat Chiyoda Tokyo 100000 Japan Hosei Univ Fac Comp & Informat Sci Tokyo 142 Japan Osaka Univ Inst Sci & Ind Res Osaka Japan

ISBN: (纸本)9783642259197

This paper presents a distributed task allocation method whose strategies are alternatively selected based on the estimated workloads of the local agents. Recent Internet. sensor-network, and cloud computing applications are large-scale and fully-distributed, and thus, require sophisticated multi-agent system technologies to enable a large number of programs and computing resources to be effectively used. To elicit the capabilities of all the agents in a large-scale multi-agent system (LSMAS) in which thousands of agents work concurrently requires a new negotiation strategy for appropriately allocating tasks in a distributed manner. We start by focusing on the contract net protocol (CNP) in LSMAS and then examine the effects of the awardee selection strategies, that is. the task allocation strategies. We will show that probabilistic awardee selections improve the overall performance in specific situations. Next, the mixed strategy in which a number of awardee selections are alternatively used based on the analysis of the bid from the local agents is proposed. Finally, we show that the proposed strategy does not only avoid task concentrations but also reduces the wasted efforts, thus it can considerably improve the performance.

关键词： distributed task allocation Adaptive Behavior Negotiation Load-balancing

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distributed task allocation Optimisation Techniques 18

Distributed Task Allocation Optimisation Techniques

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Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems

作者： Joanna Turner Loughborough University Loughborough United Kingdom

Multi-agent task allocation is a complex problem compounded by various constraints such as deadlines, agent capabilities, and communication delays. In high-stake real-time environments, such as rescue missions, it is difficult to predict in advance what the requirements of the mission will be, and what resources will be available. Yet, a fast response and speedy execution are critical to the outcome. This thesis proposes distributed optimisation techniques to tackle the following questions: how to maximise the number of assigned tasks in time restricted environments with limited resources; how to reach consensus within a reasonable time-frame; and how to allow for changeability of factors such as the availability of agents.

关键词： distributed task allocation multi-agent systems scheduling

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A Cluster-based Approach to Consensus Based distributed task allocation

A Cluster-based Approach to Consensus Based Distributed Task...

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22nd Euromicro International Conference on Parallel, distributed, and Network-Based Processing (PDP)

作者： Smith, Darren Wetherall, Jodie Woodhead, Steve Adekunle, Andrew Univ Greenwich Internet Secur Res Lab Chatham ME4 4TB Kent England

ISBN: (纸本)9781479927289

This paper presents a novel extension to the Consensus-Based Bundle Algorithm (CBBA), which we have named Cluster-Formed Consensus-Based Bundle Algorithm (CF-CBBA). CF-CBBA is designed to reduce the amount of communication required to complete a distributed task allocation process, by partitioning the problem and processing it in parallel clusters. CF-CBBA has been shown, in comparison with baseline CBBA, to require less communication when allocating tasks. Three key aspects of task allocation have been investigated;(a) the time taken to allocate tasks, (b) the amount of communication necessary to satisfy the requirements of distributed task allocation algorithms such as CBBA, and (c) the efficiency with which a collection of tasks (a mission) is completed by a group of robots (a collective).

关键词： distributed task allocation MANET cost communication cluster topology

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A distributed task allocation Method for Multi-UAV Systems in Communication-Constrained Environments

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DRONES 2024年第8期8卷 342-342页

作者： Yan, Shaokun Feng, Jingxiang Pan, Feng Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Jiangsu Automat Res Inst Lianyungang 222000 Peoples R China Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China

This paper addresses task allocation to multi-UAV systems in time- and communication-constrained environments by presenting an extension to the novel heuristic performance impact (PI) algorithm. The presented algorithm, termed local reassignment performance impact (LR-PI), consists of an improved task inclusion phase, a novel communication and conflict resolution phase, and a systematic method of reassignment for unallocated tasks. Considering the cooperation in accomplishing tasks that may require multiple UAVs or an individual UAV, the task inclusion phase can build the ordered task list on each UAV with a greedy approach, and the significance value of tasks can be further decreased and conflict-free assignments can be reached eventually. Furthermore, the local reassignment for unallocated tasks focuses on maximizing the number of allocated tasks without conflicts. In particular, the non-ideal communication factors, such as bit error, time delay, and package loss, are integrated with task allocation in the conflict resolution phase, which inevitably exist and can degrade task allocation performance in realistic communication environments. Finally, we show the performance of the proposed algorithm under different communication parameters and verify the superiority in comparison with the PI-MaxAsses and the baseline PI algorithm.

关键词： distributed task allocation performance impact UAV communication time constraint

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Game theoretic self-organization in multi-satellite distributed task allocation

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AEROSPACE SCIENCE AND TECHNOLOGY 2021年 112卷 106650-106650页

作者： Sun, Changhao Wang, Xiaochu Qiu, Huaxin Zhou, Qingrui China Acad Space Technol Qian Xuesen Lab Space Technol Youyi Rd 104 Beijing 100094 Peoples R China

This paper addresses self-organized task allocation in multi-satellite systems by formulating it as a potential game and proposing a distributed task allocation algorithm (DT2A) via learning in games. We show that each Nash equilibrium of the game constitutes a task cover that maximizes the number of executed tasks. Moreover, we also prove that the proposed DT2A converges with probability 1to near optimal assignments in finite time. Numerical experiments demonstrate the algorithm robustness against incidental disturbances and reveal the positive effect of the memory length on solution efficiency refinement. Comparison experiments in both small-scale and large-scale scenarios highlight the superiority of the presented methodology over existing typical methods that are distributed or centralized. (c) 2021 Elsevier Masson SAS. All rights reserved.

关键词： Multi-satellite system distributed task allocation Learning in games Self organization Nash equilibrium

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A Social Multi-Agent Cooperation System Based on Planning and distributed task allocation

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INFORMATION 2020年第5期11卷 271页

作者： Gharbi, Atef Northern Border Univ Fac Comp & Informat Technol Rafha 91911 Saudi Arabia Univ Carthage INSAT LISI Carthage 1054 Tunisia

Planning and distributed task allocation are considered challenging problems. To address them, autonomous agents called planning agents situated in a multi-agent system should cooperate to achieve planning and complete distributed tasks. We propose a solution for distributed task allocation where agents dynamically allocate the tasks while they are building the plans. We model and verify some properties using computation tree logic (CTL) with the model checker its-ctl. Lastly, simulations are performed to verify the effectiveness of our proposed solution. The result proves that it is very efficient as it requires little message exchange and computational time. A benchmark production system is used as a running example to explain our contribution.

关键词： distributed task allocation multi-agent system planning agent computation tree logic (CTL) model checker

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Addressing robustness in time-critical, distributed, task allocation algorithms

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APPLIED INTELLIGENCE 2019年第1期49卷 1-15页

作者： Whitbrook, Amanda Meng, Qinggang Chung, Paul W. H. Univ Derby Dept Elect Comp & Math Derby DE22 3AW England Loughborugh Univ Dept Comp Sci Loughborough LE11 3TU Leics England

The aim of this work is to produce and test a robustness module (ROB-M) that can be generally applied to distributed, multi-agent task allocation algorithms, as robust versions of these are scarce and not well-documented in the literature. ROB-M is developed using the Performance Impact (PI) algorithm, as this has previously shown good results in deterministic trials. Different candidate versions of the module are thus bolted on to the PI algorithm and tested using two different task allocation problems under simulated uncertain conditions, and results are compared with baseline PI. It is shown that the baseline does not handle uncertainty well;the task-allocation success rate tends to decrease linearly as degree of uncertainty increases. However, when PI is run with one of the candidate robustness modules, the failure rate becomes very low for both problems, even under high simulated uncertainty, and so its architecture is adopted for ROB-M and also applied to MIT's baseline Consensus Based Bundle Algorithm (CBBA) to demonstrate its flexibility. Strong evidence is provided to show that ROB-M can work effectively with CBBA to improve performance under simulated uncertain conditions, as long as the deterministic versions of the problems can be solved with baseline CBBA. Furthermore, the use of ROB-M does not appear to increase mean task completion time in either algorithm, and only 100 Monte Carlo samples are required compared to 10,000 in MIT's robust version of the CBBA algorithm. PI with ROB-M is also tested directly against MIT's robust algorithm and demonstrates clear superiority in terms of mean numbers of solved tasks.

关键词： Heuristic algorithms Multi-agent systems distributed task allocation Auction-based scheduling Robust optimization

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A distributed Algorithm for Multirobot task allocation via Weighted Buffered Voronoi Partition

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2024年第12期71卷 16098-16107页

作者： Cheng, Hao Tian, Bailing Zhang, Xuewei Shen, Hongming Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China

This article proposes a distributed bundle algorithm for task allocation problems for multirobot systems. Specifically, in the developed formulation of the vehicle routing problem with time windows (VRPTW), the robots are assigned to dispatch necessities for the survivors. The utility of each robot is evaluated by the preference index, composed of the distance cost and the task reward. Considering the requirements of the distributed structure and real-time computing, we propose the weighted buffered Voronoi partition-based bundle algorithm. The proposed algorithm dynamically updates the weighted buffered Voronoi partition (WBVP) and calculates the bundle construction once the subtask set changes. The former divides the task area into several disjoint partitions, and the latter ensures that the robot determines the scheduling for tasks according to its preference. Finally, experiment results are presented to demonstrate the effectiveness and feasibility of the proposed distributed framework.

关键词： distributed task allocation multitask Voronoi partition multirobot systems

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