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The primary target of this work is human-robot collaboration, especially for service robots in complicated application scenarios. Three assumptions and four requirements are identified. State-of-the-art, general-purpose Natural Language Processing (NLP), Commonsense Reasoning (in particular, ASP), and Robotics techniques are integrated in a layered architecture. The architecture and mechanisms have been implemented on a service robot, Ke Jia. Instead of command languages, small limited segments of natural languages are employed in spoken dialog between Ke Jia and its users. The information in the dialog is extracted, classified and transferred into inner representation by Ke Jia’s NLP mechanism, and further used autonomously in problem-solving and planning. A series of case study was conducted on Ke Jia with positive results, verifying its ability of acquiring knowledge through spoken dialog with users, autonomous solving problems by virtue of acquired causal knowledge, and autonomous planning for complex tasks.
Chen et al. (Mon,) studied this question.