As knowledge graph has the potential to bridge the gap between commonsense knowledge and reasoning over actionable capabilities of mobile robotic platforms, incorporating knowledge graph into robotic system attracted increasing attention in recent years. Previously, graph visualization has been used wildly by developers to make sense of knowledge representations. However, due to lacking the link between abstract knowledge of the real-world environment and the robot's actions, transitional visualization tools are incompatible for expert-user to understand, test, supervise and modify the graph-based reasoning system with the embodiment of the robots. Therefore, we developed an interface which enables robotic experts to send commands to the robot in natural language, then interface visualizes the procedures of the robot mapping the command to the functions for querying in the commonsense knowledge database, links the result to the real world instances in a 3D map and demonstrate the execution of the robot from the first-person perspective of the robot. After 3 weeks of usage of the system by robotic experts in their daily development, some feedback was collected, which provides insight for designing such systems.

翻译：鉴于知识图谱具备弥合常识知识与移动机器人平台可操作能力推理之间鸿沟的潜力，近年来将知识图谱融入机器人系统日益受到关注。此前，开发者广泛使用图可视化技术理解知识表征。然而，由于缺乏真实环境抽象知识与机器人动作之间的关联，传统的可视化工具难以满足专家用户理解、测试、监督和修改基于图的具身推理系统的需求。为此，我们开发了一种交互界面：机器人专家可通过自然语言向机器人发送指令，界面将可视化机器人将指令映射至常识知识库查询函数的完整过程，并将查询结果关联至三维地图中的真实世界实例，同时以机器人的第一人称视角展示其执行过程。经过机器人专家在日常开发中连续三周使用该系统后，我们收集到的反馈为同类系统的设计提供了重要启示。