A Distributed Market-based Algorithm for the Multi-robot Assignment Problem

Trigui, Sahar; Koubâa, Anis; Cheikhrouhou, Omar; Youssef, Habib; Bennaceur, Hachémi; Sriti, Mohamed–Foued; Javed, Yasir

doi:10.1016/j.procs.2014.05.540

Cited by 37 publications

(13 citation statements)

References 11 publications

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“…For heterogeneous robot completing different types of tasks, Kaleci and Parlaktuna (2012) proposed the task allocation method based on market mechanism. Trigui, Koubaa, and Cheikhrouhou (2014) thought that it can improve the work efficiency by switching tasks in the process of warehouse robots completing tasks and then proposed the extended distributed market oriented algorithm to solve the robot task allocation problem.…”

Section: Methods Based On the Market Mechanismmentioning

confidence: 99%

Task Assignment Problem of Robots in a Smart Warehouse Environment

Li¹,

Li²,

Jiang³

2016

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The task assignment problem of robots in a smart warehouse environment (TARSWE) based on cargo-to-person is investigated. Firstly, the sites of warehouse robots and the order picking tasks are given and the task assignment problem for picking one order is formulated into a mathematical model to minimize the total operation cost. Then a heuristic algorithm is designed to solve the task assignment problem for picking multiple orders. Finally, simulations are done by using the orders data of online bookstore A. The results show that using the heuristic algorithm of this paper to assign robots, the cost was reduced by 2% and it can effectively avoid far route and unbalanced workload of robots. The feasibility and validity of the model and algorithm are verified. The model and algorithm in this paper provide a theoretical basis to solve the TARSWE.

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Section: Methods Based On the Market Mechanismmentioning

confidence: 99%

Task Assignment Problem of Robots in a Smart Warehouse Environment

Li¹,

Li²,

Jiang³

2016

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“…In recent years, market-based approaches have become popular to coordinate multi-robot systems. These methods have attempted to present a distributed solution for the task allocation problem [44]. Jones et al [22] described a market based approach to task allocation for the fire fighting in a disaster response domain.…”

Section: Related Work 21 Multi-robot Allocation and Coordinationmentioning

confidence: 99%

Self-adaptive decision-making mechanisms to balance the execution of multiple tasks for a multi-robots team

et al. 2018

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This work addresses the coordination problem of multiple robots with the goal of finding specific hazardous targets in an unknown area and dealing with them cooperatively. The desired behaviour for the robotic system entails multiple requirements, which may also be conflicting. The paper presents the problem as a constrained bi-objective optimization problem in which mobile robots must perform two specific tasks of exploration and at same time cooperation and coordination for disarming the hazardous targets. These objectives are opposed goals, in which one may be favored, but only at the expense of the other. Therefore, a good trade-off must be found. For this purpose, a nature-inspired approach and an analytical mathematical model to solve this problem considering a single equivalent weighted objective function are presented. The results of proposed coordination model, simulated in a two dimensional terrain, are showed in order to assess the behaviour of the proposed solution to tackle this problem. We have analyzed the performance of the approach and the influence of the weights of the objective function under different conditions: static and dynamic. In this latter situation, the robots may fail under the stringent limited budget of energy or for hazardous events. The paper concludes with a critical discussion of the experimental results.

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“…In addition, both solutions assume perfect connections between robots. Finally, [9] proposes two distributed market-based algorithms where N tasks must be assigned to N identical robots, and where each robot can perform only one task. Again, this solution partially covers our approach.…”

Section: Related Workmentioning

confidence: 99%

Dynamic process migration in heterogeneous ROS-based environments

Cano

Molinos

Nagarajan

et al. 2015

2015 International Conference on Advanced Robotics (ICAR)

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In distributed (mobile) robotics environments, the different computing substrates offer flexible resource allocation options to perform computations that implement an overall system goal. The AnyScale concept that we introduce and describe in this paper exploits this redundancy by dynamically allocating tasks to appropriate substrates (or scales) to optimize some level of system performance while migrating others depending on current resource and performance parameters. In this paper, we demonstrate this concept with a general ROS-based infrastructure that solves the task allocation problem by optimising the system performance while correctly reacting to unpredictable events at the same time. Assignment decisions are based on a characterisation of the static/dynamic parameters that represent the system and its interaction with the environment. We instantiate our infrastructure on a case study application, in which a mobile robot navigates along the floor of a building trying to reach a predefined goal. Experimental validation demonstrates more robust performance (around a third improvement in metrics) under the Anyscale implementation framework.

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A Distributed Market-based Algorithm for the Multi-robot Assignment Problem

Cited by 37 publications

References 11 publications

Task Assignment Problem of Robots in a Smart Warehouse Environment

Task Assignment Problem of Robots in a Smart Warehouse Environment

Self-adaptive decision-making mechanisms to balance the execution of multiple tasks for a multi-robots team

Dynamic process migration in heterogeneous ROS-based environments

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