一种基于航线切片的高精度激光雷达扫描通道的形成方法
By combining sparse point cloud models with distribution network line data and employing route slicing technology, the problems of insufficient equipment resource allocation and high costs caused by high point cloud density are solved, enabling the autonomous generation of high-precision power grid routes and improving inspection efficiency.
CN116973940BActive Publication Date: 2026-07-17STATE GRID ZHEJIANG ELECTRIC POWER CO LTD SHAOXING POWER SUPPLY CO
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- STATE GRID ZHEJIANG ELECTRIC POWER CO LTD SHAOXING POWER SUPPLY CO
- Filing Date
- 2023-06-28
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing technologies require high point cloud density for unmanned aerial vehicle (UAV) inspections of power distribution lines, resulting in insufficient equipment resource allocation and efficiency improvement, and high costs.
Method used
By using a route slicing method, a channel inspection model is established by combining a sparse point cloud model with distribution network line data. This reduces point cloud density, enables high-precision power grid route generation, and reduces equipment requirements and human intervention.
Benefits of technology
It has enabled the autonomous generation of high-precision power grid routes, reducing equipment costs and human resource investment, and improving inspection efficiency and accuracy.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN116973940B_ABST
Abstract
本申请公开了一种基于航线切片的高精度激光雷达扫描通道的形成方法，包括如下步骤：S1：采集全域数据，根据全域数据建立全域模型；S2：获取配网线路数据，根据配网线路数据对全域模型进行切片，建立通道巡检模型；S3：根据通道巡检模型进行最优化计算，输出最优扫描路线。本申请的有益效果：以稀点云模型建立全域模型，降低点云密度从而降低成本，同时以高密度电网信息点云与低密度地理信息点云共存，实现稀点云模型高精度通道巡检模型的建立，从而满足高精度电网航线生成的同时无需采集全域高点云密度，降低成本。
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