This work presents an advanced inspection system utilizing Boston Dynamics' Spot for autonomous industrial monitoring in collaboration with TSMC. The system integrates Routing System, Multi-Map navigation, and digital twin simulation through NVIDIA Isaac Sim to enhance operational efficiency in large-scale environments. By combining these technologies, we establish a scalable, memory-efficient, and highly reliable framework for autonomous industrial inspection.
The inspection process begins with user-defined task assignments, which are processed by an intelligent routing system that determines optimal navigation paths. The routing system employs:
Once optimal routes are established, the navigation commands are relayed to the multi-map navigation system, which facilitates seamless movement across different factory sections.
Large factory environments pose challenges in handling comprehensive maps. To address this, we developed a map-switching system utilizing AprilTag markers as positional reference points. This system:
By partitioning large spaces into manageable sub-maps and leveraging AprilTag-assisted positioning, we enable reliable and efficient navigation throughout extensive factory environments.
Spot employs an onboard 3D LiDAR sensor to continuously scan its surroundings, generating high-resolution point cloud data. This real-time data is cross-referenced with pre-established environmental maps using the 3D Normal Distributions Transform (NDT) algorithm
Beyond physical navigation, Spot has been integrated into a digital twin environment via NVIDIA Isaac Sim. This enables: