Abstract

Staff safety is not assured due to the indoor substation’s high environmental risk factor. The Chinese State Grid Corporation has been engaged in the intelligentization of substations and the employment of robots for inspection tasks. The autonomous navigation and positioning system of the mobile chassis is the most important feature of this type of robot, as it allows the robot to perceive the surrounding environment information at the initial position using its own sensors and find a suitable path to move to the target point to complete the task. Automatic navigation is the basis for the intelligentization of indoor substation robots, which is of great significance to the efficient and safe inspection of indoor substations. Based on this, this paper formulates a new navigation system, and builds a chassis simulation environment in the Robot Operating System (ROS). To begin with, we develop a novel hardware and sensor-based chassis navigation system experimental platform. Secondly, to conduct the fusion of the odometer and inertial navigation data, the Extended Kalman Filter (EKF) is used. The map’s creation approach determines how the environmental map is created. The global path is scheduled with the A* algorithm, whereas the local path is scheduled with the Dynamic Window Method (DWA). Finally, the created robot navigation system is applied to an auxiliary operation robot chassis suited for power distribution cabinet switch and the navigation system’s experimental analysis is conducted using this platform, demonstrating the system’s efficacy and practicability.

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