Design and deployment of an large language model-enhanced autonomous robot for intelligent operation and maintenance in data centers

The exponential growth of global data demands unprecedented reliability and efficiency of data center operations. Traditional manual inspection methods remain inefficient and error-prone. This article presents an autonomous mobile robot enhanced by large language models and hierarchical three-dimensional scene graphs for intelligent operation and maintenance. The core innovation lies in enabling semantic-aware navigation, allowing the robot to interpret high-level instructions like “inspect servers with the red alert light on in cold aisle B” by leveraging the three-dimensional scene graph for spatial-semantic reasoning and the large language model for task parsing. Deployed in multiple ultra-large data centers, the system has improved inspection efficiency by over 50%, autonomously patrolled over 10,000 km, and identified more than 1200 equipment anomalies. This work demonstrates a significant step towards fully autonomous, intelligent infrastructure management.