In this paper, we present a new method for a swarm to collectively sense and follow a gradient in the environment. The agents in the swarm only rely on relative distance and bearing measurements of neighbors. Additionally, only a minority of agents in the swarm perceive the scalar value of the gradient at their location. We test the method with incrementally changing ratio of agents with sensors on various swarm sizes. In addition to repeated simulation experiments, we also test the performance with a real nano-drone swarm. Results show us that, using the new method, the swarm was successful at following the gradient in the environment even with a low portion of the swarm with sensors on various swarm sizes. A real nano-drone swarm also demonstrates a good performance in our test even with members having disabled sensors.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Collective Gradient Following with Sensory Heterogeneous UAV Swarm


    Additional title:

    Springer Proceedings in Advanced Robotics


    Contributors:

    Conference:

    International Symposium on Distributed Autonomous Robotic Systems ; 2022 ; Montbéliard, France November 28, 2022 - November 30, 2022



    Publication date :

    2024-02-01


    Size :

    15 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Collective gradient perception with a flying robot swarm

    TURGUT, ALİ EMRE / Karaguzel, Tugay Alperen / Eiben, A. E. et al. | BASE | 2023

    Free access

    Shinerbot: Bio-Inspired Collective Robot Swarm Navigation Platform

    Luo, Enyu / Fang, Xin Hui / Ng, Yuting et al. | British Library Conference Proceedings | 2016


    Stable Belief Estimation in Shepherd-Assisted Swarm Collective Decision Making

    Hussein, Aya / Abbass, Hussein A. | Springer Verlag | 2021


    Towards a Heterogeneous Swarm for Object Classification

    Arnold, Ross / Abruzzo, Benjamin / Korpela, Christopher | IEEE | 2019


    Autonomous and Collective Intelligence for UAV Swarm in Target Search Scenario

    Giacomossi, Luiz / Souza, Flavio / Cortes, Raphael Gomes et al. | IEEE | 2021