Multi-sensor asynchronous information fusion system and method for substation inspection robot
An inspection robot and multi-sensor technology, applied in the field of robot navigation, can solve the problems of no substation inspection robot navigation design, etc., to achieve the effect of enriching navigation decisions, improving navigation accuracy and work efficiency
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Embodiment 1
[0056] A preferred embodiment of the present invention provides a multi-sensor asynchronous information fusion method for a substation inspection robot. The multi-sensor asynchronous information fusion method for a substation inspection robot in this embodiment includes: a sensor, a processor, a memory, and a storage device. The computer program in the memory and operable on the processor, for example, a program of a substation inspection robot multi-sensor asynchronous information fusion method, the method includes the following steps:
[0057] Step 1: Obtain the data information of the substation environment through different sensors, including the lidar point cloud information and visible light image information of the environment. The laser radar sensor is a two-dimensional laser radar sensor.
[0058] Step 2: Train the deep learning semantic segmentation model for the substation environment, and segment the visible light image information through the model;
[0059] Step...
Embodiment 2
[0078] This embodiment provides a substation inspection robot multi-sensor asynchronous information fusion system, including an electronic device connected to the substation inspection robot terminal equipment, characterized in that: the electronic device includes an environmental data acquisition module, a model Training module, sensor data matching and fusion module, fused data output module;
[0079] The environmental data acquisition module acquires environmental information of the substation;
[0080] The model training module trains the deep learning semantic segmentation model to obtain the substation environment semantic segmentation model;
[0081] After the data acquisition module obtains the visible light data of the substation environment, it is input into the model training module substation environment semantic segmentation model, and the substation environment picture information containing semantic information is obtained;
[0082] The sensor data matching and...
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