Aug 2026· Message Understanding Conference· pp. 293-305· 0 citations· 39 references
Computer Science
Abstract
Smart environments allow for rich, context-specific interactions. Additionally, the introduction of agentic AI gives UX designers new ways to create flexible, human-centered interactions. However, given the complexity of these environments, building them remains challenging. Classical methods for mitigating the complexity of prototyping behavior, e.g., Wizard-of-Oz prototyping, cannot adequately represent the flexibility and adaptivity necessary for such environments. We present AIKitchen, an open-source framework for prototyping user experiences in agentic, context-driven environments. This framework allows designers to rapidly create, evaluate, and iterate complex interaction scenarios. We demonstrate this approach in the context of a smart kitchen, which integrates environmental sensors, smart-home appliances, and robotic actuators. Through a series of examples, we show how designers can integrate various contextual sensors, actuators, and agents, orchestrate system behavior, and explore different interaction scenarios. This makes the framework valuable for designing context-aware, room-scale experiences and exploring what our future in smart environments might look like.
This work adapts Hugging Face's SmolVLA for Universal Robots lightweight robots, and releases the open-source repository ROS2SmolVLA that implements an interface for ROS 2 to SmolVLA, and makes it applicable for industrial-grade hardware.
Nils Mandischer, Noah Böckmann, Ludwig Holl et al.· 0 citations
This work introduces a unified formalism for proactive robot assistance, organize it into three levels, and provides a framework to address the highest level of unprompted proactive assistance, and presents a method, GAP, that instantiates the framework, learning from passive observation to anticipate user goals and ac...
This analysis shows that the modularity, flexibility, and reactivity of classical BTs are insufficient for adaptation needs involving runtime restructuring, reasoning under uncertainty, mission reinterpretation, learning, or integration with external knowledge and planning mechanisms.
Human-Robot Interaction (HRI) presents significant challenges in accurately assessing situations, adapting robotic behavior to human intentions, ensuring explainability, pertinence, and acceptability, and effectively managing uncertainty. Traditional model-based approaches provide reliability but struggle with human un...
Luigi Gargioni, Rachid Alami, D. Fogli· International Journal of Soc...· 0 citations
This study introduces an interdisciplinary framework for benchmarking robots deployed in public environments, addressing the gap between traditional laboratory metrics and real-world benchmarking requirements. We evaluate three distinct robots across diverse use cases - outdoor park cleaning, pedestrian underpass clean...
Raphael Memmesheimer, Martina Overbeck, Dominik Beyer et al.· 0 citations
Adaptive behavior is a fundamental requirement for social robots operating in real-world environments, where interactions must dynamically respond to both observable actions and inferred user states. In this work, we propose a novel framework that models human–robot interaction as a planning problem, where adaptive con...
Giulia Berettieri, Anna Allegra Bixio, Lucrezia Grassi et al.· Companion Publication of the...· 0 citations
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