Abstract
Human visual inspection of drains is laborious, time-consuming, and prone to accidents. This work presents an AI-enabled robot-assisted remote drain inspection and mapping framework using our in-house developed reconfigurable robot Raptor. The four-layer IoRT serves as a bridge between the users and the robots, through which seamless information sharing takes place. The Faster RCNN ResNet50, Faster RCNN ResNet101, and Faster RCNN Inception-ResNet-v2 deep learning frameworks were trained using a transfer learning scheme with six typical concrete defect classes and deployed in an IoRT framework remote defect detection task. The efficiency of the trained CNN algorithm and drain inspection robot Raptor was evaluated through various real-time drain inspection field trials using the SLAM technique. The experimental results indicate that robot’s maneuverability was stable, and its mapping and localization were also accurate in different drain types. Finally, for effective drain maintenance, the SLAM-based defect map was generated by fusing defect detection results in the lidar-SLAM map.
Highlights
Drains are the primary conduits transporting sewage, rainwater, and other liquid waste to the point of disposal in any urban environment
The efficiency of the proposed system was tested through a robot maneuverability test, drain defect detection, and defect mapping accuracy
The reconfigurable robot was tested in three different drain environments in maneuverability tests: s2, V type, and flat terrain drains
Summary
Drains are the primary conduits transporting sewage, rainwater, and other liquid waste to the point of disposal in any urban environment. Computer vision-based robot-assisted remote inspection is a widely used method in the industry and has been classified into two categories: the traditional approach (non-learning) and the learningbased approach. CCTV and fixed morphology robot are widely used tools for computer vision-based robot-assisted drain inspection and defect mapping application [13,14,15,16,23,24]. This work presents an AI-enabled robot-assisted remote drain inspection and defect mapping using our in-house developed reconfigurable robot Raptor. This reconfigurable robot is specially designed for inspecting complex drain environments with the help of a DL algorithm and the SLAM technique and generates a SLAM-based defect map.
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