## 2 Related Works
### Joint Attention in HRI
Compared to a baseline with random gaze, the coordinated strategy improved task efficiency and spatial clarity. The results showed enhanced communication dynamics and greater perceptions of sociability and competence. [PERSON] et al. [32] explored how young children responded to a robot's attentional cues during a word-learning task. Using DragonBot [[https://robots.media.mit.edu/portfolio/dragonbot/](https://robots.media.mit.edu/portfolio/dragonbot/)]([https://robots.media.mit.edu/portfolio/dragonbot/](https://robots.media.mit.edu/portfolio/dragonbot/)) (accessed on 30 July 2025), the robot turned its gaze and body toward one of two images while naming the target. Children aged 2-5 interpreted these cues effectively and identified the correct referent, performing comparably to those with a human partner. The results demonstrate that socially contingent verbal and non-verbal behaviors in robots can guide attention and support early learning in naturalistic settings. In this line, [PERSON] et al. [33] deployed an autonomous robot to promote social engagement and JA in children with autism. The robot initiated interaction using storytelling, games, and gaze-based cues. All the sessions were video-recorded and annotated to assess JA behaviors before and after the intervention. The study found significant increases in JA episodes not only during robot interaction but also in generalization to human partners, demonstrating that robot-initiated attentional behaviors can produce lasting transferable social effects. [PERSON] et al. [34] explored a JA system combining gaze and user action perception to enhance social presence during collaborative problem-solving. In the MagPuzzle task, the participants interacted with a humanoid robot under proactive or responsive gaze conditions. The robot dynamically adjusted its attention to participants' focus in the responsive mode. Evaluated via the Social Presence Questionnaire, the results showed significantly higher scores in the responsive condition, particularly in perceived attentiveness and intention understanding, underlining how responsive gaze mechanisms nurture engagement and strengthen perceived social capabilities in HRI. Furthermore, [PERSON] et al. [35] conducted a comparative study evaluating how children with and without autism responded to JA behaviors from a robot versus a human interlocutor. Using the NAO robot [[https://aldebaran.com/en/nao6/](https://aldebaran.com/en/nao6/)]([https://aldebaran.com/en/nao6/](https://aldebaran.com/en/nao6/)) (accessed on 30 July 2025), the authors implemented gaze shifts and pointing gestures to evoke both RJA and IJA. The interactions were recorded and analyzed using a structured behavioral coding scheme. Although the children responded more consistently to human cues, the robot successfully evoked JA behaviors across the groups, suggesting that robots can function as valid attention-directing agents in diverse developmental contexts. Similarly, [PERSON] and [PERSON] [36] introduced a planning-based Gaze Control System (GCS) to enhance JA, turn-taking, and intimacy regulation in multi-party HRI. Implemented on the Furhat robot [[https://www.furhatrobotics.com/furhat-robot](https://www.furhatrobotics.com/furhat-robot)]([https://www.furhatrobotics.com/furhat-robot](https://www.furhatrobotics.com/furhat-robot)) (accessed on 30 July 2025), the GCS coordinated head and eye movements by prioritizing gaze targets over time using a dynamic planning mechanism. In a collaborative card-sorting game, the participants interacted with either the GCS or a reactive baseline. The study showed that the planning-based system improved the naturalness and interpretability of gaze, better regulated social distance, and enhanced the fluidity and depth of interactions, highlighting the value of planned gaze behavior for socially attuned robot conduct. A two-session experimental design was used by [PERSON] [16] to explore how JA influences trust in HRI.