Morten Roed Frederiksen

Tactile regulation with pocket-sized robots: reducing movement and heart rate in children through hand-held interaction

Periods of heightened arousal or restlessness can interfere with children’s ability to remain physically calm in everyday settings such as classrooms. Handheld tactile technologies may offer a simple and engaging way to support brief moments of structured sensory-motor engagement. This paper investigates how a pocket-s...

When Bigger Is Not Better: LLM Scale and User Perception in Short-Duration Social Human-Robot Interaction

Toward Self-Repairing Ubiquitous Robots Using Goal-Oriented Agentic AI in Human-Robot Interactions

Ubiquitous robotic systems often lack traditional visual interfaces, making natural language interaction important for maintenance and repair. This paper presents a goal-oriented agentic AI architecture that enables non-expert users to complete technical repair tasks through situated dialogue. The architecture separate...

Diminishing Returns of Intelligence: The Non-Linear Relationship Between LLM Scale and User Perception in Short-Duration Open-Ended Social Human-Robot Interactions

Overall, the findings indicate diminishing returns from model scaling in brief open-ended social HRI, where conversational flow, responsiveness, and socially appropriate behavior potentially matter as much as raw parameter count.

Toward User-Mediated Self-Repair in Ubiquitous Robots Through Goal-Oriented Agentic AI

Ubiquitous robotic systems often lack traditional visual interfaces, necessitating resilient natural language interaction for maintenance and repair tasks. This paper presents a goal oriented agentic AI architecture designed to enable non-expert users to perform technical repairs through situated dialogue. The framewor...

A Goal-Oriented Agentic Framework For Collaborative Branching Human-Robot Interactions

It is suggested that the benefit of the agentic framework lies primarily in interaction quality rather than conversational efficiency, and the agentic architecture displayed robustness by recovering from non-normative inputs while maintaining strict goal alignment.