论文标题
可靠且低的延迟同步中间件，用于共同模拟异质多机器人系统
A Reliable and Low Latency Synchronizing Middleware for Co-simulation of a Heterogeneous Multi-Robot Systems
论文作者
论文摘要
搜索和救援，野火监测以及洪水/飓风影响评估是最近的IoT网络关键任务服务。通信同步，可靠性和最小通信抖动是基于时间的物理ROS模拟器，基于事件的基于网络的无线模拟器的主要模拟和系统问题，以及部署在实际环境中的移动和异构物联网设备的复杂动力学。由于同步物理（机器人）和网络模拟器，在部署之前很难模拟异质多机器人系统。由于其基于主的体系结构，大多数基于TCP/IP的同步中间Wares都使用ROS1。具有无用数据包发现的实时ROS2体系结构同步机器人和无线网络模拟。使用数据分配服务（DDS）的速度感知传输控制协议（TCP）技术，用于地面和空中机器人，出版物订阅运输最小化数据包丢失，同步，传输和通信抖动。凉亭和NS-3模拟和测试。模拟器 - 敏捷的中间件。 LOS/NLOS和TCP/UDP协议测试了我们基于ROS2的同步中间件，用于数据包损耗概率和平均延迟。一项彻底的消融研究用实时无线网络模拟器Emane和基于主的ROS1的无主ROS2取代了NS-3。最后，我们使用一台空中无人机（Duckiedrone）和两辆地面车辆（Turtlebot3汉堡）在不同地形（ROS2）和启用主人（ROS1）集群的不同地形上测试了网络同步和抖动。我们的中间件表明，具有多种固定和机器人设备的大规模物联网基础设施可以实现低延迟通信（模拟和真实的降低12％和11％），同时满足关键任务应用程序的可靠性（10％和15％的数据包损失）和高保真要求。
Search and rescue, wildfire monitoring, and flood/hurricane impact assessment are mission-critical services for recent IoT networks. Communication synchronization, dependability, and minimal communication jitter are major simulation and system issues for the time-based physics-based ROS simulator, event-based network-based wireless simulator, and complex dynamics of mobile and heterogeneous IoT devices deployed in actual environments. Simulating a heterogeneous multi-robot system before deployment is difficult due to synchronizing physics (robotics) and network simulators. Due to its master-based architecture, most TCP/IP-based synchronization middlewares use ROS1. A real-time ROS2 architecture with masterless packet discovery synchronizes robotics and wireless network simulations. A velocity-aware Transmission Control Protocol (TCP) technique for ground and aerial robots using Data Distribution Service (DDS) publish-subscribe transport minimizes packet loss, synchronization, transmission, and communication jitters. Gazebo and NS-3 simulate and test. Simulator-agnostic middleware. LOS/NLOS and TCP/UDP protocols tested our ROS2-based synchronization middleware for packet loss probability and average latency. A thorough ablation research replaced NS-3 with EMANE, a real-time wireless network simulator, and masterless ROS2 with master-based ROS1. Finally, we tested network synchronization and jitter using one aerial drone (Duckiedrone) and two ground vehicles (TurtleBot3 Burger) on different terrains in masterless (ROS2) and master-enabled (ROS1) clusters. Our middleware shows that a large-scale IoT infrastructure with a diverse set of stationary and robotic devices can achieve low-latency communications (12% and 11% reduction in simulation and real) while meeting mission-critical application reliability (10% and 15% packet loss reduction) and high-fidelity requirements.
