Several deployment locations of mobile robotic systems are human made (i.e. urban firefighter, building inspection, property security) and the manager may have access to domain-specific knowledge about the place, which can provide semantic contextual information allowing better reasoning and decision making. In this paper we propose a system that allows a mobile robot to operate in a location-aware and operator-friendly way, by leveraging semantic information from the deployment location and integrating it to the robots localization and navigation systems. We integrate Building Information Models (BIM) into the Robotic Operating System (ROS), to generate topological and metric maps fed to an layered path planner (global and local). A map merging algorithm integrates newly discovered obstacles into the metric map, while a UWB-based localization system detects equipment to be registered back into the semantic database. The results are validated in simulation and real-life deployments in buildings and construction sites.
翻译:移动机器人系统的若干部署地点是人造的(即城市消防员、建筑物检查、财产安全),管理人员可能能够获得有关该地点的具体领域知识,从而能够提供语义背景信息,从而更好地进行推理和决策。在本文件中,我们提议建立一个系统,通过利用部署地点的语义信息并将其纳入机器人定位和导航系统,使移动机器人能够以易于定位和操作的方式运作。我们将建筑信息模型(BIM)纳入机器人操作系统(ROS),以生成供分层路径规划员(全球和地方)使用的地形图和计量图。地图合并算法将新发现的障碍纳入通用图中,而基于世行的本地化系统则检测设备将重新登记在语义数据库中。结果在建筑物和建筑工地的模拟和实时部署中得到验证。