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:由于知识图有潜力缩小对移动机器人平台可操作能力的常识知识和推理之间的差距,将知识图纳入机器人系统近年来引起越来越多的注意。以前,图形可视化被开发者狂妄地用于了解知识的表述方式,但由于对真实世界环境的抽象知识与机器人行动之间缺乏联系,专家用户无法用机器人的化身理解、测试、监督和修改基于图表的推理系统,因此,我们开发了一个界面,使机器人专家能够用自然语言向机器人发送指令,然后将机器人对指令进行绘图的程序与在普通知识数据库查询的功能进行可视化,将结果与3D地图中的真实世界情况联系起来,并从机器人的第一人的角度展示机器人的运行情况。在机器人专家在日常开发过程中使用该系统3周之后,收集了一些反馈,为设计这种系统提供了洞察力。