ANT (Amenities Navigation Technology) responds to today’s housing crisis with a logistics-based solution utilising autonomous, distributed robots to reconfigure private and shared interior spaces to negotiate the requirements of inhabitants. Inspired by space stations where all surfaces are utilised and warehouse robotics, the project embeds a continuous system of rails for robots to navigate, distribute, and store spatial elements and furniture across walls, ceilings, and floors in a continuously adaptive building life cycle. A series of robots were designed and evolved via sequential prototypes testing the constraints of the system. The architectural system employs a controlled set of continuous curvatures enabling robots to access all interior surfaces. Robotic agents were trained in a simulator using deep reinforcement learning to learn collaborative space planning policies while navigating the rail system. Cellular automata research was developed exploring neighbourhood relationships to influence the configuration of space in the design process. A spatial assembly algorithm generates continuous building assemblages. An agent-based pedestrian algorithm was developed to simulate the changing building states in relation to dynamic occupancy. Finally, augmented and virtual reality was leveraged in a custom platform allowing people living in the building to interact with and influence their spaces enabling shared space optimisation while considering each user’s unique lifestyle.