| 基于slam技术与位置融合的换流站主设备虚拟现实巡检方法 |
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| 引用本文：张瑞亮，吕刚，方明，李兵，罗宗源.基于slam技术与位置融合的换流站主设备虚拟现实巡检方法[J].计算技术与自动化,2024,(3):153-158 |
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| 中文摘要:提出基于slam技术与位置融合的换流站主设备虚拟现实巡检方法，改善巡检路径规划效果。基于智能机器人的换流站主设备虚拟现实巡检框架，利用智能机器人携带的IMU采集其加速度、角速率数据，经模糊自适应PI算法补偿智能机器人的航向角误差后，获取其位姿估计结果；采用相机、激光雷达传感器采集换流站环境图像数据，并基于双目结构光的RGB-Dslam方法对其作处理，以获取相机位姿估计；采用扩展卡尔曼滤波实现智能机器人的融合定位，确定其各时刻位置点、方向角，将其同步到虚拟空间后，绘制出换流站环境地图，以启发式路径搜索方法确定最优巡检路径，依据最小化成本函数制定巡检避障策略，实现换流站主设备虚拟空间避障巡检轨迹规划。实验结果表明：该方法可完成机器人航向角误差补偿；规划出最优换流站主设备巡检路线，误差仅为厘米级。 |
| 中文关键词:slam技术 位置融合 换流站主设备 虚拟现实 模糊自适应PI 扩展卡尔曼滤波 |
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| Virtual Reality Inspection Method for Main Equipment of Converter Station Based on Slam Technology and Position Fusion |
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| Abstract:A virtual reality inspection method for main equipment of converter station based on slam technology and position fusion is proposed to improve the inspection path planning effect. Based on the virtual reality inspection framework of the main equipment of the converter station of the intelligent robot, the IMU carried by the intelligent robot is used to collect its acceleration and angular rate data. After the fuzzy adaptive PI algorithm compensates the heading angle error of the intelligent robot, the position and attitude estimation results are obtained. The camera and lidar sensor are used to collect the environmental image data of the converter station, and the RGB-Dslam method based on binocular structured light is used to process it to obtain the camera pose estimation. The extended Kalman filter is used to realize the fusion positioning of intelligent robots, determine their position points and direction angles at all times, and after synchronizing them to the virtual space, draw the environment map of the converter station. The heuristic path search method is used to determine the optimal inspection path, and the inspection and obstacle avoidance strategy is formulated according to the minimum cost function, so as to realize the obstacle avoidance inspection path planning of the virtual space of the main equipment of the converter station. The experimental results show that the method can compensate the robot’s heading angle error. The optimal inspection route of the main equipment of the converter station is planned, and the error is only centimeter level. |
| keywords:slam technology position fusion main equipment of converter station virtual reality fuzzy adaptive PI extended Kalman filter |
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