This project aims to develop an interactive control system for an autonomous service robot using an ROS (robot operating system). The system integrates an intuitive web interface and an interactive chatbot supported by Google Gemini to enhance the control experience and personalization for the user. The methodology includes the integration of an API (application programming interface) to access a database storing user preferences, such as speed and frequent destinations. Furthermore, the system employs facial recognition, people groups’ recognition, and adaptive responses from the chatbot for autonomous navigation, ensuring a service tailored to the individual needs of each user. To validate the proposal, it was implemented on an autonomous service robot, integrated into a motorized wheelchair. Tests demonstrated that the system effectively adjusts the wheelchair’s behavior to user preferences, resulting in safer and more personalized navigation. The use of facial recognition and chatbot interaction provided more intuitive and efficient control. The developed system significantly improves the autonomy and quality of life for wheelchair users, proving to be a viable and efficient solution for autonomous and personalized control. The results indicate that integrating technologies like ROS, intuitive web interfaces, and interactive chatbots can transform the user experience of autonomous wheelchairs, better meeting the specific needs of users.