Abstract
The term understandable robots refers to robots making their actions and intentions understandable (or explainable) to humans. To support understandability of a team of collaborating robots we use natural language to let the robots verbalize what they do and plan to do. Our solution is based on Cooperating Distributed Grammar Systems for plan derivation and a Multi-agent algorithm for coordination of robot actions. We implemented and evaluated our solution on a team of three Pepper robots that work collaboratively to move an object on a table, thereby coordinating their capabilities and actions and verbalizing their actions and intentions. In a series of experiments, our solution not only successful demonstrated collaboration and task fulfilment, but also considerable variation, both regarding actions and generated natural language utterances.
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Singh Kumar, A., Baranwal, N., Richter, K.F., Hellström, T., Bensch, S.: Understandable collaborating robot teams. In: 18th International Conference on Practical Applications of Agents and Multi-agent Systems (2020). Submitted
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Singh, A.K., Baranwal, N., Richter, KF., Hellström, T., Bensch, S. (2020). Understandable Teams of Pepper Robots. In: Demazeau, Y., Holvoet, T., Corchado, J., Costantini, S. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection. PAAMS 2020. Lecture Notes in Computer Science(), vol 12092. Springer, Cham. https://doi.org/10.1007/978-3-030-49778-1_43
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DOI: https://doi.org/10.1007/978-3-030-49778-1_43
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