| 基于机器视觉的配网带电作业机器人障碍物识别 |
 点此下载全文 |
| 引用本文：牛振勇1 ，钟晓蓥2，卢蓬锋2，郭嘉伟2，江东游2.基于机器视觉的配网带电作业机器人障碍物识别[J].计算技术与自动化,2024,(3):148-152 |
| 摘要点击次数: 166 |
| 全文下载次数: 0 |
|
|
| 中文摘要:人眼长时间进行障碍物识别容易出现疲劳，导致障碍物识别误差大，因此提出了基于机器视觉的配网带电作业机器人障碍物识别。通过带电作业机器人搭载的相机，精准采集配网作业时的连续帧图像。利用多尺度Harris亚像素角点检测算法。提取图像特征点，并通过改进的k-d树最近邻搜索算法匹配特征点，得到匹配特征点对。建立机器人运动变换模型，并通过自适应滤波与阈值分割结合的方法，抑制自运动补偿后图像的背景信息，提取障碍物目标，完成障碍物识别。实验证明：该方法可有效采集配网作业时的图像，并且特征点匹配效果较好，障碍物识别结果与实际情况一致。 |
| 中文关键词:机器视觉 配电网 带电作业 机器人 障碍物识别 特征点提取 |
| |
| Robot Obstacle Recognition for Live Operation in Distribution Network Based on Machine Vision |
|
|
| Abstract:Human eyes are prone to fatigue when identifying obstacles for a long time, resulting in large error in obstacle identification. Therefore, a machine vision based obstacle identification method for live working robots in distribution networks is proposed. The camera carried by the live working robot accurately captures continuous frame images during distribution network operations. Using multi-scale Harris subpixel corner detection algorithm, image feature points are extracted and matched using an improved k-d tree nearest neighbor search algorithm to obtain matching feature point pairs. Establish a robot motion transformation model, and combine adaptive filtering and threshold segmentation to suppress the background information of the image after motion compensation, extract obstacle targets, and complete obstacle recognition. Experiments show that this method can effectively collect images during distribution network operations, and the feature point matching effect is good. The obstacle recognition results are consistent with the actual situation. |
| keywords:machine vision distribution network live working robot obstacle identification feature point extraction |
| 查看全文 查看/发表评论 下载pdf阅读器 |
次