## 4 Experimental Setup
### Social Robot Mini  
Mini is a desktop social robot designed for close face-to-face interactions, developed at the RoboticsLab of the University Carlos III of Madrid [54]. Mini features a friendly appearance, as shown in Figure 2, with a design intended for HRI. Its physical structure includes five degrees of freedom distributed across its head, neck, torso, and arms, enabling it to perform natural and dynamic gestures. Expressive LEDs are embedded in its cheeks, heart, and mouth to emulate effective human expressions and interaction and enhance its social presence. To perceive the user and its environment, Mini is equipped with an Intel RealSense D435i RGB-D [[https://www.intelrealsense.com/depth-camera-d435i/](https://www.intelrealsense.com/depth-camera-d435i/)]([https://www.intelrealsense.com/depth-camera-d435i/](https://www.intelrealsense.com/depth-camera-d435i/)) (accessed on 30 July 2025), which captures color and depth information. Additionally, sensory capabilities include capacitive touch sensors on its torso and arms to detect physical interactions and microphones in its head and body to capture ambient sound and the user's voice. Two internal speakers placed in Mini's head are used for verbal communication, and two screens in its eyes allow Mini to emulate eye blinking and gaze. Moreover, Mini has an auxiliary tablet that can play multimedia content and acts as an additional way to communicate with the robot. To reduce CPU usage during computational tasks, Mini integrates AI accelerators such as the Intel Movidius Neural Compute Stick 2 (NCS2) [[https://www.intel.la/content/www/xl/es/products/sku/140109/intel-neural-compute-stick-2/specifications.html](https://www.intel.la/content/www/xl/es/products/sku/140109/intel-neural-compute-stick-2/specifications.html)]([https://www.intel.la/content/www/xl/es/products/sku/140109/intel-neural-compute-stick-2/specifications.html](https://www.intel.la/content/www/xl/es/products/sku/140109/intel-neural-compute-stick-2/specifications.html)) (accessed on 30 July 2025) and Google Coral TPU [[https://coral.ai/products/accelerator](https://coral.ai/products/accelerator)]([https://coral.ai/products/accelerator](https://coral.ai/products/accelerator)) (accessed on 30 July 2025), allowing it to perform real-time operations. Specifically, the head pose estimation model runs on the NCS2, while the body pose estimation is delegated to the Coral TPU. The face detector and the hand detector run on CPU. Mini's software architecture is built upon the Robot Operating System (ROS) [55] and is composed of a set of modular components that collectively support perception, decision-making, and actuation during human-robot interaction. The system starts by acquiring sensory data through the robot's RGB-D camera, which feeds into a series of visual detectors responsible for extracting user-related features such as head position, orientation, and hand gestures. These features are processed by the Perception Manager, which standardizes the information and transmits it to the RJAS. The RJAS prioritizes the most salient stimuli based on these cues, estimates the user's FoA, and triggers a responsive behavior that includes coordinated eye, head, and torso movements to reorient the robot towards that FoA. This attentional information is also sent to the human-robot Interaction Manager, which coordinates verbal responses and expressive gestures, and to the Decision-Making System, which selects the appropriate skill to execute based on the current interaction state. The robot has multiple skills that consist of interactive games and behaviors that enhance engagement and stimulate the user both cognitively and physically. The selected behavior is then carried out by the Actuation module, which manages the robot's motor actions and expressive outputs. For a more detailed explanation of the integration of the RJAS within Mini's architecture, see [20].