As embodied intelligence emerges as a core frontier in artificial intelligence research, simulation platforms must evolve beyond low-level physical interactions to capture complex, human-centered social behaviors. We introduce FreeAskWorld, an interactive simulation framework that integrates large language models (LLMs) for high-level behavior planning and semantically grounded interaction, informed by theories of intention and social cognition. Our framework supports scalable, realistic human-agent simulations and includes a modular data generation pipeline tailored for diverse embodied tasks.To validate the framework, we extend the classic Vision-and-Language Navigation (VLN) task into a semantically enriched Direction Inquiry setting, wherein agents can actively seek and interpret navigational guidance. We present and publicly release FreeAskWorld, a large-scale benchmark dataset comprising reconstructed environments, six diverse task types, 16 core object categories, 63,429 annotated sample frames, and more than 17 hours of interaction data to support training and evaluation of embodied AI systems. We benchmark VLN models, and human participants under both open-loop and closed-loop settings. Experimental results demonstrate that models fine-tuned on FreeAskWorld outperform their original counterparts, achieving enhanced semantic understanding and interaction competency. These findings underscore the efficacy of socially grounded simulation frameworks in advancing embodied AI systems toward sophisticated high-level planning and more naturalistic human-agent interaction.

Robot morphology-the form, body shape, and structure of robots-makes up a key design space in human-robot interaction (HRI), shaping how robots function, express themselves, and interact with humans. Yet, despite its importance, little is known about how design frameworks might guide form exploration and generation. To address this gap, we introduce Elements of Robot Morphology, a design framework that identifies five fundamental elements: intelligence, kinematics, end effectors, locomotion, and structure. Based on an analysis of robots in the IEEE robot database, this framework provides a foundation for exploring diverse robot forms. To operationalize the framework, we developed Morphology Exploration Blocks (MEB), a set of tangible blocks that enable designers to physically build and experiment with different morphologies, fostering hands-on and collaborative exploration. We evaluated the framework and toolkit through a case study and a series of design workshops, demonstrating their support for analysis, ideation, reflection, and collaborative creation in robot design.

In this late-breaking report, we present our design process motivated to build tangible, cost-effective, child- and family-friendly social robot prototypes aimed to (1) support the practical needs of families, as well as (2) serve as a feasible research platform to mitigate technical and logistical challenges faced within conducting inhome HRI studies. We apply a research through design approach, combined with participatory design methods, to produce functional prototypes. In future work, we are preparing to continue improving prototype design by conducting (1) iterative co-design sessions with artists and product designers focusing on the hardware design, (2) iterative co-design sessions with families focusing on the interaction design, and (3) long-term technology probe studies in homes to evaluate the effectiveness of the technological platform. We aim to solicit feedback from the HRI community on our design process and prototype research platform.