Controlling Industrial Robots with High-Level Verbal Commands
Controlling Industrial Robots with High-Level Verbal Commands
复制标题
使用高级口头命令控制工业机器人
DOI：
10.1007/978-3-030-90525-5_19
复制
发表时间：
2021
期刊：
影响因子：
1.3
通讯作者：
Jung
中科院分区：
文献类型：
--
作者：
Dongkyu Choi;Wei Shi;Yinghuai Liang;Kheng Hui Yeo;Jung
今天的工业机器人仍然主要是预先编程来执行特定任务。尽管学术界之前对人机交互进行了研究，但在工业环境中采用此类系统并非易事，而且很少有人这样做。在本文中，我们介绍了一个机器人系统，我们控制高层次的口头命令，利用一些最新的神经方法来语言理解和认知架构的目标导向，但反应式执行。我们表明，大规模的预训练语言模型可以有效地进行微调，将口头指令翻译成机器人任务，比其他语义解析方法更好，并且我们的系统能够通过对话处理人机交互过程中发生的各种异常，包括未知任务，用户中断和世界状态的变化。
Industrial robots today are still mostly pre-programmed to perform a specific task. Despite previous research in human-robot interaction in the academia, adopting such systems in industrial settings is not trivial and has rarely been done. In this paper, we introduce a robotic system that we control with high-level verbal commands, leveraging some of the latest neural approaches to language understanding and a cognitive architecture for goal-directed but reactive execution. We show that a large-scale pre-trained language model can be effectively fine-tuned for translating verbal instructions into robot tasks, better than other semantic parsing methods, and that our system is capable of handling through dialogue a variety of exceptions that happen during human-robot interaction including unknown tasks, user interruption, and changes in the world state.