Swarm robotic systems, unlike traditional multi-robotic systems, deploy number of cost effective robots which can co-operate, aggregate to form patterns/formations and accomplish missions beyond the capabilities of individual robot. In the event of fire, mine collapse or disasters like earthquake, swarm of robots can enter the area, conduct rescue operations, collect images and convey locations of interest to the rescue team and enable them to plan their approach in advance. Task allocation among members of the swarm is a critical and challenging problem to be addressed. DTTA- a distributed, Time-division multiple access (TDMA) based task allocation framework is proposed for swarm of robots which can be utilised to solve any of the 8 different types of task allocation problem identified by Gerkey and Mataric´. DTTA is reactive and supports task migration via extended task assignments to complete the mission in case of failure of the assigned robot to complete the task. DTTA can be utilised for any kind of robot in land or for co-operative systems comprising of land robots and air-borne drones. Dependencies with other layers of the protocol stack were identified and a quantitative analysis of communication and computational complexity is provided. To our knowledge this is the first work to be reported on task allocation for clustered scalable networks suitable for handling all 8 types of multi-robot task allocation problem. Effectiveness and feasibility of deploying DTTA in real world scenarios is demonstrated by testing the framework for two diverse application scenarios.


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    Title :

    DTTA - Distributed, Time-division Multiple Access based Task Allocation Framework for Swarm Robots


    Contributors:

    Publication date :

    2017-04-25


    Remarks:

    doi:10.14429/dsj.67.10955
    Defence Science Journal; Vol 67 No 3; 316-324 ; 0976-464X ; 0011-748X



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629




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