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A distributed task allocation method for heterogeneous UAVs in dynamic and communication-constrained environments

JOURNAL OF SUPERCOMPUTING 2025年第1期81卷 1-32页

作者： Yan, Shaokun Xia, Yuanqing Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Jiangsu Automat Res Inst Lianyungang 222000 Peoples R China Zhongyuan Univ Technol Zhengzhou 450007 Peoples R China

This paper considers the multiple unmanned aerial vehicle (UAV) task allocation problem in dynamic and communication-constrained environments, where limited resources, non-ideal communication factors, deadlines and newly added tasks are considered. Given the complex constraints, the task allocation problem is modeled mathematically. The proposed method builds upon the performance impact (PI) algorithm, extending it with an improved task inclusion phase, a novel conflict resolution phase and a systematic way of clustering while preserving the robust convergence property. In addition, a coalition formation method is presented to cope with the newly added tasks or the tasks that cannot be completed by a single UAV after repeating the task inclusion phase and conflict resolution phase. Numerical simulations are constructed to illustrate the procedure and superiority of the proposed method compared with the state-of-the-art distributed task allocation algorithms. The proposed method is not only effective in increasing the number of tasks with resource requirements satisfied but also efficient in saving the number of iterations and communication events to converge.

关键词： distributed task allocation Performance impact UAV Communication Resource constraint

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distributed task allocation with critical tasks and limited capacity

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ROBOTICA 2021年第11期39卷 2008-2032页

作者： Zhang, An Yang, Mi Bi, Wenhao Gao, Fei Northwestern Polytech Univ Sch Aeronaut Xian Peoples R China CETC Res Inst 20 Key Lab Data Link Technol Xian Peoples R China

This paper considers the task allocation problem under the requirement that the assignments of some critical tasks must be maximized when the network capacity cannot accommodate all tasks due to the limited capacity for each unmanned aerial vehicle (UAV). To solve this problem, this paper proposes an extended performance impact algorithm with critical tasks (EPIAC) based on the traditional performance impact algorithm. A novel task list resizing phase is developed in EPIAC to deal with the constraint on the limited capacity of each UAV and maximize the assignments of critical tasks. Numerical simulations demonstrate the outstanding performance of EPIAC compared with other algorithms.

关键词： distributed task allocation Extended performance impact algorithm Limited capacity Critical tasks Multi-UAV system

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distributed task allocation and Planning Under Temporal Logic and Communication Constraints

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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年第7期9卷 6536-6543页

作者： Chen, Ziyang Li, Lin Kan, Zhen Univ Sci & Technol China Dept Automat Hefei 230026 Peoples R China

It is challenging to coordinately allocate and plan the tasks of a heterogeneous multi-agent system in a shared workspace. It can be even more challenging if the agents are subject to limited communication capability (i.e., exchange information with nearby agents only) and complex tasks with temporal and logic constraints. Motivated by these practical challenges, a distributed task allocation and planning method is developed, in which each agent communicates with neighboring agents about the task information (i.e., the preference of sub-tasks to be executed and the estimated task completion time) and predicts the task information of agents out of the communication range. Based on the collected task information, each agent can independently make conflict-free planning to improve the execution efficiency of the task. Rigorous analysis shows that the generated plan is guaranteed to be conflict free and numerical experiments demonstrate the effectiveness of the planned tasks.

关键词： task analysis Resource management Planning Costs Robot kinematics Multi-agent systems Collision avoidance Linear temporal logic distributed task allocation task planning heterogeneous multi-agent systems

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distributed task allocation Optimisation Techniques 17

Distributed Task Allocation Optimisation Techniques

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17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS)

作者： Turner, Joanna Loughborough Univ Loughborough Leics England

ISBN: (纸本)9781450356497

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 Scheduling Multi-Agent Systems

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distributed task allocation in multi-robot systems using argumentation-based negotiation

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2nd International Conference on Advanced Material Research (ICAMR 2012)

作者： Lolu, Irina Stanescu, Aurelian Moisescu, Mihnea Sacala, Ioan Stefan Univ Politehn Bucuresti Fac Automat Control & Comp Sci Bucharest Romania

ISBN: (纸本)9783037853634

The continuous growing of application's complexity and increased interest in automated negotiation brought recently researcher's attention to persuasive negotiation (PN) and argumentation-based negotiation (ABN). The Market-based approach has gained popularity in the last decade due to its flexibility, speed and robustness. Contract Net protocol inspired algorithms have been proved suitable for allocating weakly coupled tasks in robot teams, but there are still some challenges when addressing complex application in uncertain environments. In this context the purpose of the paper is to present a method to allocate tasks in multi-robot systems through the use of augmentation- based negotiation.

关键词： multi-robot systems distributed task allocation

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distributed task allocation with Time Constraints under Limited Communication Resources 1n Multi-Agent System 14

Distributed Task Allocation with Time Constraints under Limi...

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14th Asian Control Conference (ASCC)

作者： Li, Weilin Wu, Jing Long, Chengnian Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

ISBN: (纸本)9798331540845;9789887581598

In this paper, a new distributed allocation algorithm based on performance impact with collective influence (PI-CI) is proposed. Considering inefficiency of creating time slots in PI-MaxAss, two completely independent phases with different communication frequencies are designed to ensure allocation both realtime and conflict-free under limited communication. To solve the misconvergence of the baseline algorithm PI-MaxAss in allocation results, an evaluation function is put forward in consensus phase to directly determines the final attribution of repeatedly assigned tasks, guaranteeing convergence of allocation. Comparison experiments validate the performance improvement of the PI-CI algorithm over the baseline algorithm.

关键词： distributed task allocation multi-agent system limited communication resources collective influence

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distributed task allocation and task Sequencing for Robotswith Motion Constraints

Distributed Task Allocation and Task Sequencing for Robotswi...

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作者： Sadeghi Yengejeh, Armin University of Waterloo

学位级别：master

This thesis considers two routing and schedulingproblems. The first problem is task allocation and sequencing formultiple robots with differential motion constraints. Each task isdefined as visiting a point in a subset of the robot configurationspace ?– this definition captures a variety of tasks includinginspection and servicing, as well as one-in-a-set tasks. Ourapproach is to transform the problem into a multi-vehiclegeneralized traveling salesman problem (GTSP). We analyze the GTSPinsertion methods presented in literature and we provide bounds onthe performance of the three insertion mechanisms. We then developa combinatorial-auction-based distributed implementation of theallocation and sequencing algorithm. The number of the bids in acombinatorial auction, a crucial factor in the runtime, is shown tobe linear in the size of the tasks. Finally, we present extensivebenchmarking results to demonstrate the improvement over existingdistributed task allocation methods. In the second part of thisthesis, we address the problem of computing optimal paths throughthree consecutive points for the curvature-constrained forwardmoving Dubins vehicle. Given initial and final configurations ofthe Dubins vehicle and a midpoint with an unconstrained heading,the objective is to compute the midpoint heading that minimizes thetotal Dubins path length. We provide a novel geometrical analysisof the optimal path and establish new properties of the optimalDubins'' path through three points. We then show how our method canbe used to quickly refine Dubins TSP tours produced usingstate-of-the-art techniques. We also provide extensive simulationresults showing the improvement of the proposed approach in bothruntime and solution quality over the conventional method ofuniform discretization of the heading at the mid-point, followed bysolving the minimum Dubins path for each discreteheading

关键词： Autonomous vehicles distributed task allocation Nonholonomic motion planning

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A resource-constrained distributed task allocation method based on a two-stage coalition formation methodology for multi-UAVs

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JOURNAL OF SUPERCOMPUTING 2022年第7期78卷 10025-10062页

作者： Yang, Mi Zhang, An Bi, Wenhao Wang, Yunong Northwestern Polytech Univ Sch Aeronaut Xian 710072 Shaanxi Peoples R China

The task allocation problem is an important research field in unmanned aerial vehicles (UAVs). However, most existing task allocation algorithms can form coalitions to address the resources constraints, but cannot support starting tasks at the same time, nor can cope with the new emerging tasks flexibly. To this end, we propose a novel resource-constrained task allocation method based on the performance impact algorithm (RCPIA) to support simultaneously starting tasks and provide more flexibility to reallocate the new tasks. More specifically, based on the proposed task allocation model, we firstly modify the task inclusion phase and conflict resolution phase of the baseline PI algorithm to preferentially allocate the tasks to the UAVs that can complete tasks individually. After that, to make full use of resources and further allocate remaining unassigned tasks, a two-stage coalition formation method is creatively proposed to form a coalition for the tasks that cannot be performed by a single UAV to provide enough resources. Especially, an idle time slot mechanism (ITSM) is investigated to shift the start times of tasks that can be performed by a single UAV to create a longer feasible time slot to insert the task. Thirdly, the reassignment application of the two-stage coalition method is introduced to cope with new emerging tasks. Finally, numerical simulations are constructed to illustrate the procedure of RCPIA and verify the superiority of RCPIA compared with other task allocation algorithms in efficiency and success allocation rate.

关键词： Multi-UAV System distributed task allocation Resource constraint Coalition formation Dynamic environment

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A Heuristic distributed task allocation Method for Multivehicle Multitask Problems and Its Application to Search and Rescue Scenario

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IEEE TRANSACTIONS ON CYBERNETICS 2016年第4期46卷 902-915页

作者： Zhao, Wanqing Meng, Qinggang Chung, Paul W. H. Cardiff Univ Cardiff Sch Engn Cardiff CF24 3AA S Glam Wales Univ Loughborough Dept Comp Sci Loughborough LE11 3TU Leics England

Using distributed task allocation methods for cooperating multivehicle systems is becoming increasingly attractive. However, most effort is placed on various specific experimental work and little has been done to systematically analyze the problem of interest and the existing methods. In this paper, a general scenario description and a system configuration are first presented according to search and rescue scenario. The objective of the problem is then analyzed together with its mathematical formulation extracted from the scenario. Considering the requirement of distributed computing, this paper then proposes a novel heuristic distributed task allocation method for multivehicle multitask assignment problems. The proposed method is simple and effective. It directly aims at optimizing the mathematical objective defined for the problem. A new concept of significance is defined for every task and is measured by the contribution to the local cost generated by a vehicle, which underlies the key idea of the algorithm. The whole algorithm iterates between a task inclusion phase, and a consensus and task removal phase, running concurrently on all the vehicles where local communication exists between them. The former phase is used to include tasks into a vehicle's task list for optimizing the overall objective, while the latter is to reach consensus on the significance value of tasks for each vehicle and to remove the tasks that have been assigned to other vehicles. Numerical simulations demonstrate that the proposed method is able to provide a conflict-free solution and can achieve outstanding performance in comparison with the consensus-based bundle algorithm.

关键词： distributed task allocation multitask multivehicle overall objective search and rescue

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A distributed task allocation Algorithm for a Multi-Robot System in Healthcare Facilities

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2015年第1期80卷 33-58页

作者： Das, Gautham P. McGinnity, Thomas M. Coleman, Sonya A. Behera, Laxmidhar Univ Ulster Intelligent Syst Res Ctr Coleraine BT48 7JL Londonderry North Ireland Indian Inst Technol Dept Elect Engn Kanpur 208016 Uttar Pradesh India

Various ambient assisted living (AAL) technologies have been proposed for improving the living conditions of elderly people. One of them is to introduce robots to reduce dependency on support staff. The tasks commonly encountered in a healthcare facility such as a care home for elderly people are heterogeneous and are of different priorities. A care home environment is also dynamic and new emergency priority tasks, which if not attended shortly may result in fatal situations, may randomly appear. Therefore, it is better to use a multi-robot system (MRS) consisting of heterogeneous robots than designing a single robot capable of doing all tasks. An efficient task allocation algorithm capable of handling the dynamic nature of the environment, the heterogeneity of robots and tasks, and the prioritisation of tasks is required to reap the benefits of introducing an MRS. This paper proposes Consensus Based Parallel Auction and Execution (CBPAE), a distributed algorithm for task allocation in a system of multiple heterogeneous autonomous robots deployed in a healthcare facility, based on auction and consensus principles. Unlike many of the existing market based task allocation algorithms, which use a time extended allocation of tasks before the actual execution is initialised, the proposed algorithm uses a parallel auction and execution framework, and is thus suitable for highly dynamic real world environments. The robots continuously resolve any conflicts in the bids on tasks using inter-robot communication and a consensus process in each robot before a task is assigned to a robot. We demonstrate the effectiveness of the CBPAE by comparing its simulation results with those of an existing market based distributed multi-robot task allocation algorithm and through experiments on real robots.

关键词： Ambient assisted living Robots in healthcare facilities Multi-robot systems Multi-robot task allocation distributed task allocation Market based task allocation

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