HMAS：实现无人机、四足机器人与人类操作员之间的无缝协作及高效空间感知
HMAS: enabling seamless collaboration between drones, quadruped robots, and human operators with efficient spatial awareness
AI总结：
本文提出基于ROS 2的通用软件架构HMAS，用于集成无人机、四足机器人与人类操作员实现无缝协作，并通过实验验证RTK-GPS可满足未知室外环境中的空间感知与定位精度需求。
摘要：
配备多模态传感器的异构机器人（例如无人机、轮式和腿式地面机器人）提供了丰富且互补的功能，可帮助人类操作员在未知环境中完成复杂任务。然而，无缝集成异构智能体并使其交互与协作仍然面临挑战性问题。本文定义了一种基于ROS 2的软件架构，该架构能够以通用方式构建具身异构多智能体系统（HMAS）。我们通过一个集成空中无人机、四足机器人和人类操作员的场景展示了其有效性（参见https://youtu.be/iOtCCticGuk）。此外，智能体在未知室外环境中的空间感知是实现自主个体运动、交互和协作的关键步骤。通过密集的实验测量，RTK-GPS被证明是实现所需定位精度的合适解决方案。
英文摘要：
Heterogeneous robots equipped with multi-modal sensors (e.g., UAV, wheeled and legged terrestrial robots) provide rich and complementary functions that may help human operators to accomplish complex tasks in unknown environments. However, seamlessly integrating heterogeneous agents and making them interact and collaborate still arise challenging issues. In this paper, we define a ROS 2 based software architecture that allows to build incarnated heterogeneous multi-agent systems (HMAS) in a generic way. We showcase its effectiveness through a scenario integrating aerial drones, quadruped robots, and human operators (see https://youtu.be/iOtCCticGuk). In addition, agent spatial awareness in unknown outdoor environments is a critical step for realizing autonomous individual movements, interactions, and collaborations. Through intensive experimental measurements, RTK-GPS is shown to be a suitable solution for achieving the required locating accuracy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
