Substation equipment inspection is necessary for the power industry. With the dramatic increase in the number of substations, unmanned substations are required by the industry. This paper presents SmartGuard, a completely autonomous robotic system that can inspect substation equipment. SmartGuard consists of a robot and a data center. The robot can patrol in a substation and inspect equipment with a visible-light camera and an infrared thermograph. The acquired images and temperature information are analyzed by the data center. The data center can fuse infrared and visible-light images and find abnormal hot spots and abnormal appearance. There are 13 SmartGuards currently serving 12 substations, some of which have been working for more than 2 years. The feedback from the field shows that SmartGuard significantly improves the efficiency and reliability of substation inspection. C 2011 Wiley Periodicals, Inc.
In this study, an autonomous robot navigation system is designed for live working on distribution line. The developed system features a real‐time detection and motion planning system, incorporating a manipulator capable of grasping power components. In order to accurately identify targets, the authors propose an object detection method based on the Larger Scale ‘You Only Look Once’ Version 4 (LS‐YOLOv4) algorithm for detecting the insulators and drop fuses. The LS‐YOLOv4 extracts features of power components by Convolutional Neural Network (CNN), and then performs feature fusion. Then the authors develop a motion planning method based on the Node Control Optimal Rapidly Exploring Random Trees (NC‐RRT*), which can drive the robot to realise the autonomous robot motion planning and obstacle avoidance. On the grasping function, the authors present a reliable Lightweight‐based Convolutional Neural Network (L‐CNN) grasping point detection method. Finally, the authors evaluate fully autonomous robotic system in both simulated and real‐world experiments. The experimental results demonstrate that the proposed system can effectively identify the target and complete the grasping task in an efficient way. Notably, the proposed motion planning method can take into account both planning efficiency and accuracy to manipulation tasks.
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