The conventional human–robot interactions of robotic navigation systems must rely on strict language instructions and numerous button operations. In this study, a cloud-based dialog navigation agent (CDNA) system was designed for a campus navigation robot (CNR) that provides navigation services to students, school visitors, and people with impaired vision. The CDNA is based on a lightweight belief–desire–intention (BDI) software architecture (i.e., CellS, a cell-inspired efficient software framework), which is a goal-oriented and dynamic parallel framework. The proposed CDNA system has the following three primary functions: (1) conversational navigation service, (2) immediate path planning and path modification, and (3) location guide and place evaluation. The system can be applied to regional navigation guidance services such as campus tours. The CellS-based CDNA uses a natural language processing (NLP) technology to analyze the semantics of user statements and uses dialog to eliminate ambiguity in language to improve interaction with users. In this study, 15 items for three different navigation systems were evaluated, which demonstrated that the CDNA is advantageous in terms of interactivity and usability. The CellS-based CDNA can achieve an average speedup of 1.75 times in seven data sets. Therefore, the CDNA possesses the following advantages: high interactivity, high usability, and high performance.