6 accepted papers
Our work investigates how social robots can act in a user-aware manner by adapting their behaviour to users' personal characteristics and preferences without unnecessarily exposing them to frustration through the robot's actions. In particular, we investigate how implicit social signals inadvertentl…
Visual Place Recognition (VPR) in mobile robotics enables robots to localize themselves by recognizing previously visited locations using visual data. While the reliability of VPR methods has been extensively studied under conditions such as changes in illumination, season, weather and viewpoint, th…
Multimodal interaction plays a vital role in human–AI interaction, enabling robots or AI agents to interpret human input from multiple sensory channels and respond through diverse communication modalities. This paper introduces SHAF, an LLM-based multimodal model capable of handling text, image, and…
Visual Place Recognition (VPR) in mobile robotics enables robots to localize themselves by recognizing previously visited locations using visual data. While the reliability of VPR methods has been extensively studied under conditions such as changes in illumination, season, weather and viewpoint, th
Our work investigates how social robots can efficiently collaborate with human users in a user-aware manner, minimising the generated frustration in human colleagues, thus enhancing their experience. As part of this, we develop a useraware framework for human-robot collaborative learning. We model u
Generating emotional bodily expressions for culturally competent robots has been gaining increased attention to enhance the engagement and empathy between robots and humans in a multi-culture society. In this paper, we propose an incremental learning model for selecting the user's representative or…