Many social robots deployed in public spaces hide hybrid cognitive architectures for dealing with daily tasks. Mostly, two main blocks sustain these hybrid architectures for robot behavior generation: deliberative and behavioral-based mechanisms. Robot Operating System offers different solutions for implementing these blocks, however, some issues arise when both are released in the robot. This paper presents a software engineering approach for normalizing the process of integrating them and presenting them as a fully cognitive architecture named MERLIN. Providing implementation details and diagrams for established the architecture, this research tests empirically the proposed solution using a variation from the challenge defined in the SciRoc @home competition. The results validate the usability of our approach and show MERLIN as a hybrid architecture ready for short and long-term tasks, showing better results than using a by default approach, particularly when it is deployed in highly interactive scenarios.
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MERLIN a Cognitive Architecture for Service Robots
OpenAlex · AI-based Problem Solving and Planning · 2020
Abstract
Many social robots deployed in public spaces hide hybrid cognitive architectures for dealing with daily tasks. Mostly, two main blocks sustain these hybrid architectures for robot behavior generation: deliberative and behavioral-based mechanisms. Robot Operating System offers different solutions for implementing these blocks, however, some issues arise when both are released in the robot. This paper presents a software engineering approach for normalizing the process of integrating them and presenting them as a fully cognitive architecture named MERLIN. Providing implementation details and diagrams for established the architecture, this research tests empirically the proposed solution using a variation from the challenge defined in the SciRoc @home competition. The results validate the usability of our approach and show MERLIN as a hybrid architecture ready for short and long-term tasks, showing better results than using a by default approach, particularly when it is deployed in highly interactive scenarios.