Autotarget*: A Distributed Robot Operating System Framework for Autonomous Aerial Swarms | IEEE Conference Publication | IEEE Xplore

Autotarget*: A Distributed Robot Operating System Framework for Autonomous Aerial Swarms


Abstract:

Robot Operating System (ROS) has proven itself as a viable framework for developing robot-related applications. It offers features such as hardware abstraction, low-level...Show More

Abstract:

Robot Operating System (ROS) has proven itself as a viable framework for developing robot-related applications. It offers features such as hardware abstraction, low-level device support, inter-process communication, and useful libraries for autonomous robot systems. Concerning aerial robots, commonly called unmanned aerial vehicles (UAV) or drones, ROS provides unfortunately very basic functions. Moreover, it does not guarantee real-time operation, as it runs under Linux. Consequently, it is difficult to implement advanced ROS applications that involve a swarm of drones that need to communicate with each other to carry out a common mission. This paper proposes an extended version of the ROS framework called autotarget*, which provides a set of efficient functions designed for distributed operation on multiple UAVs flying at the same time. autotarget* relies on a multi-tier architecture with a decentralized communication layer, enabling intra-UAV messaging as well as the scalability of swarm UAVs. It has a set of daemons whose feature is to regulate the swarm's consensus control and failover policy to ensure convergence towards a common goal. Experiments with real-world swarms revealed that autotarget* is portable and satisfies the performance requirements for collaborative mission applications. We further conducted a coverage planning mission using the parallel back-and-forth algorithm, which demonstrated the efficiency of the framework in terms of time and energy. Our work should pave the way for an open-source environment dedicated to simplifying collaborative ROS application development, particularly for multi-UAV systems.
Date of Conference: 24-27 June 2024
Date Added to IEEE Xplore: 26 July 2024
ISBN Information:
Conference Location: New York, NY, USA

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