From Technical Metrics to User Perception: A User Study of a Multimodal Human-Robot Interaction System for Object Detection and Grasping
arXiv:2607.00530v1 Announce Type: cross Abstract: Improvements in the technical performance of human--robot interaction (HRI) systems do not automatically translate into differences that human users can detect during live interaction. This paper investigates whether a 15 percentage point gain in end-to-end task success (from 75% in a multimodal baseline system to 90% in an improved configuration identified through a prior ablation study) is sufficient to produce consistent and measurable differences in user perception. The baseline system combines Whisper for speech recognition, Florence-2 for
The proliferation of complex AI systems in human-robot interaction necessitates a deeper understanding of user perception beyond purely technical metrics, a critical step for practical deployment.
This study highlights the gap between technical AI performance and human perception, suggesting that user experience will be a key differentiator and bottleneck for real-world HRI adoption.
The focus shifts from raw algorithmic performance to the perceptible impact of improvements on user experience, influencing design and evaluation methodologies for HRI systems.
- · HRI system developers focusing on user experience
- · AI agents and large multimodal model integrators
- · Robotics companies prioritizing human-centered design
- · Academic researchers in human-robot interaction
- · HRI systems with poor user interfaces
- · Developers solely focused on marginal technical gains
- · Companies neglecting user testing in robotics
System design and evaluation will increasingly incorporate user perception metrics alongside technical benchmarks for HRI applications.
This focus on user perception could accelerate the development of more intuitive and adaptable robotic systems for various applications.
Successful integration of enhanced user perception may broaden public acceptance and accelerate the deployment of autonomous systems in daily life and industry.
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Read at arXiv cs.AI