  In this paper, we introduce a robotic agent specifically designed to analyze
external environments and address participants' questions. The primary focus of
this agent is to assist individuals using language-based interactions within
video-based scenes. Our proposed method integrates video recognition technology
and natural language processing models within the robotic agent. We investigate
the crucial factors affecting human-robot interactions by examining pertinent
issues arising between participants and robot agents. Methodologically, our
experimental findings reveal a positive relationship between trust and
interaction efficiency. Furthermore, our model demonstrates a 2\% to 3\%
performance enhancement in comparison to other benchmark methods.
