This graduation project focused on improving the user experience of map generation, editing, and management within the Fleet Management Control (FMC) platform for Autonomous Mobile Robots (AMRs) developed by Continental Automotive. As AMRs depend on accurate indoor maps for efficient operations, the project addressed usability gaps, poor visual hierarchy, and steep learning curves in the existing system. Research methods included user interviews, heuristic evaluations, and competitor benchmarking, leading to the identification of key personas such as deployment engineers and warehouse managers. An iterative UX approach was used to design modular workflows for map generation, cleaning, stitching, node and POI management. The solution introduced task-based workflows, modular editing tools, and clear visual feedback to reduce cognitive load. The project delivered validated wireframes, detailed UX documentation, and a future roadmap, setting a usability benchmark for enterprise AMR mapping tools and gaining recognition in internal global reviews.