RoboticsLab, Universidad Carlos III de Madrid, 28911 Leganés, Spain.
Sensors (Basel). 2022 Jul 13;22(14):5248. doi: 10.3390/s22145248.
A robust perception system is crucial for natural human-robot interaction. An essential capability of these systems is to provide a rich representation of the robot's environment, typically using multiple sensory sources. Moreover, this information allows the robot to react to both external stimuli and user responses. The novel contribution of this paper is the development of a perception architecture, which was based on the bio-inspired concept of being integrated into a real social robot. In this paper, the architecture is defined at a theoretical level to provide insights into the underlying bio-inspired mechanisms and at a practical level to integrate and test the architecture within the complete architecture of a robot. We also defined mechanisms to establish the most salient stimulus for the detection or task in question. Furthermore, the attention-based architecture uses information from the robot's decision-making system to produce user responses and robot decisions. Finally, this paper also presents the preliminary test results from the integration of this architecture into a real social robot.
强大的感知系统对于自然的人机交互至关重要。这些系统的一个基本能力是提供机器人环境的丰富表示，通常使用多个传感器源。此外，这些信息还使机器人能够对外部刺激和用户响应做出反应。本文的新颖贡献在于开发了一种感知架构，该架构基于生物启发的概念，被集成到一个真正的社交机器人中。在本文中，该架构在理论层面上进行了定义，以深入了解潜在的生物启发机制，在实践层面上进行了集成和测试，以将架构整合到机器人的完整架构中。我们还定义了机制来确定检测或任务的最显著刺激。此外，基于注意力的架构使用来自机器人决策系统的信息来生成用户响应和机器人决策。最后，本文还介绍了将此架构集成到真实社交机器人中的初步测试结果。
