This paper addresses the problem of detecting possible misbehavior in a group of autonomous mobile robots, which coexist in a shared environment and interact with each other and coordinate according to a set of common interaction rules. Such rules specify what actions each robot is allowed to perform in order to interact with the other members of the group. The rules are distributed, i.e., they can be evaluated only starting from the knowledge of the individual robot and the information the robot gathers from neighboring robots. We consider misbehaving those robots which, because of either spontaneous failures or malicious tampering, do not follow the rules and whose behavior thus deviates from the nominal assigned one. The main contribution of the paper is to provide a methodology to detect such misbehavior by observing the congruence of actual behavior with the assigned rules as applied to the actual state of the system. The presented methodology is based on a consensus protocol on the events observed by robots. The methodology is fully distributed in the sense that it can be performed by individual robots based only on the local available information, it has been theoretically proven and validated with experiments involving real aerial heterogeneous robots.


    Access

    Download


    Export, share and cite



    Title :

    Distributed motion misbehavior detection in teams of heterogeneous aerial robots



    Publication date :

    2015-01-01



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    MISBEHAVIOR DETECTION AND INTERVENTION

    ADITHTHAN ARUN / ISLAM MD MHAFUZUL / PERANANDAM PRAKASH M et al. | European Patent Office | 2025

    Free access


    Coordinated perception by teams of aerial and ground robots

    Grocholsky, Benjamin P. / Swaminathan, Rahul / Kumar, Vijay et al. | SPIE | 2004


    MISBEHAVIOR DETECTION IN AUTONOMOUS DRIVING COMMUNICATIONS

    YANG LIUYANG LILY / SASTRY MANOJ R / LIU XIRUO et al. | European Patent Office | 2020

    Free access

    Edge Assisted Misbehavior Detection for Platoons

    Kan, Xinyue / Ganlath, Akila / Ucar, Seyhan et al. | IEEE | 2019