In today's rapidly evolving world, service robots are assuming critical roles in diverse fields, ranging from manufacturing, agriculture to healthcare. These mobile robots are required to process advanced navigation capabilities, allowing them to move seamlessly within multi-floor layouts. While traditional navigation solutions have excellent development in guiding robots through single-level environments, the challenge lies in enabling autonomous robots to understand the structural elements connecting different floors, such as elevators and stairs. The research work addressing these problems has been developed in collaboration with the LINKS Foundation, that conducts exploration across various domains, such as AI, IoT, Cyber-physical and autonomous systems. This thesis aims to investigate existing navigation approaches and explore novel solutions to recognize and interact with the environment (e.g., with automated doors, furniture, and elevators) to enable navigation across floors in a building using autonomous ground vehicle(AGV).