AI-Powered Robotics for Culvert and Sewer Inspections
Published Mar. 26, 2025
The inspection of sewer and culvert infrastructure has long been a time-consuming and labor-intensive process, often requiring manual assessment in challenging and hazardous environments. However, advancements in deep learning and robotics are transforming the way these critical systems are monitored and maintained.
By deploying state-of-the-art deep learning algorithms in robotic systems, we can automate defect detection in real-time, enhancing accuracy, efficiency, and safety. These intelligent systems not only streamline inspections but also enable proactive maintenance, reducing costs and preventing failures before they become critical.
- Robotic system for automated inspections: Advancements in robotics and artificial intelligence, automated inspection systems are transforming the way we monitor and maintain essential infrastructure. Clearpath Jackal is a lightweight, fast, and easy-to-use unmanned ground vehicle (UGV) designed for ROS Noetic. Equipped with a range of advanced sensors, including LIDAR, cameras, and GPS, Jackal enables real-time data collection and precise environment mapping. This robotic system enhances efficiency, accuracy, and safety by autonomously navigating complex terrains and detecting infrastructure deficiencies in sewers and culverts.
- Deployment of AI models on robotic platforms: By running deep learning models, robotic systems can detect and analyze structural deficiencies in real time, reducing the need for manual inspections. For deployment, the deep learning model is first trained and saved locally. A Robot Operating System (ROS) package is then developed to load the pre-trained model onto a GPU for inference, enabling real-time processing. The model's output is efficiently processed and displayed on-screen, with a performance of 20 FPS. This seamless integration of AI models with robotic platforms enables real-time defect detection, data pre-processing, and visualization, ultimately transforming infrastructure inspection into a faster, safer, and more intelligent process.
- Control center for robotic systems: As robotic inspection systems become more complex, a centralized Control Center becomes necessary for efficient monitoring and management. The Control Center enables operation of the Clearpath Jackal robotic system, allowing users to track robot status, deploy AI models, and oversee inspections with precision. Operators can monitor critical modules such as motors, bridges, battery levels, and other essential systems in real time, ensuring optimal performance. The system supports the deployment of AI-powered inspection models like PipeWatch AI for detecting structural deficiencies with high accuracy. A live data visualization interface provides real-time footage from the robot’s camera alongside AI-generated inspection outputs, offering an intuitive inspection experience. Users can initiate, manage, and control the entire inspection process remotely, streamlining operations. Additionally, the Control Center generates detailed inspection reports required for maintenance planning and infrastructure assessment. By integrating real-time monitoring, AI-powered inspections, and automated reporting, the Control Center enhances efficiency, accuracy, and reliability in robotic inspections.
