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Enhancing Robot Explanation Capabilities through Vision-Language Models: a Preliminary Study by Interpreting Visual Inputs for Improved Human-Robot Interaction
David Sobr\'in-Hidalgo, Miguel \'Angel Gonz\'alez-Santamarta, \'Angel Manuel Guerrero-Higueras, Francisco Javier Rodr\'iguez-Lera, Vicente Matell\'an-Olivera
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Enhancing Robot Explanation Capabilities through Vision-Language Models: a Preliminary Study by Interpreting Visual Inputs for Improved Human-Robot Interaction
This paper presents an improved system based on our prior work, designed to create explanations for autonomous robot actions during Human-Robot Interaction (HRI). Previously, we developed a system that used Large Language Models (LLMs) to interpret logs and produce natural language explanations. In this study, we expand our approach by incorporating Vision-Language Models (VLMs), enabling the system to analyze textual logs with the added context of visual input. This method allows for generatin…