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A platform for research: civil engineering, architecture and urbanism
Building robot based on multi-sensor fusion and positioning method thereof
The invention discloses a building robot based on multi-sensor fusion and a positioning method thereof, and belongs to the technical field of building robotics.The building robot comprises a robot body, a laser radar, a binocular camera, an inertial measurement unit and an unscented Kalman filter, the laser radar is used for acquiring three-dimensional point cloud data of the surrounding environment; the binocular camera is used for acquiring image data of the surrounding environment; the inertial measurement unit is used for acquiring dynamic data of the robot body; the unscented Kalman filter is used for converting the three-dimensional point cloud data, the image data and the dynamic data into the same coordinate system and producing a positioning result of the robot body in real time; according to the building robot positioning method based on multi-sensor fusion, the advantages of various sensors such as the laser radar, the binocular camera and the inertial measurement unit are integrated, so that the building robot can complete high-precision self-positioning in indoor or outdoor complex environments.
本发明公开了一种基于多传感器融合的建筑机器人及其定位方法，属于建筑机器人技术领域，建筑机器人包括机器人本体以及设置于其上的激光雷达、双目相机、惯性测量单元和无迹卡尔曼滤波器，激光雷达用于获取周围环境的三维点云数据；双目相机用于获取周围环境的图像数据；惯性测量单元用于获取机器人本体的动态数据；无迹卡尔曼滤波器用于将三维点云数据、图像数据和动态数据转化到相同的坐标系，实时生产机器人本体的定位结果；本发明中的基于多传感器融合的建筑机器人的定位方法，通过整合激光雷达、双目相机和惯性测量单元多种传感器的优势，可使建筑机器人无论在室内还是室外复杂环境中完成高精度的自主定位。
Building robot based on multi-sensor fusion and positioning method thereof
The invention discloses a building robot based on multi-sensor fusion and a positioning method thereof, and belongs to the technical field of building robotics.The building robot comprises a robot body, a laser radar, a binocular camera, an inertial measurement unit and an unscented Kalman filter, the laser radar is used for acquiring three-dimensional point cloud data of the surrounding environment; the binocular camera is used for acquiring image data of the surrounding environment; the inertial measurement unit is used for acquiring dynamic data of the robot body; the unscented Kalman filter is used for converting the three-dimensional point cloud data, the image data and the dynamic data into the same coordinate system and producing a positioning result of the robot body in real time; according to the building robot positioning method based on multi-sensor fusion, the advantages of various sensors such as the laser radar, the binocular camera and the inertial measurement unit are integrated, so that the building robot can complete high-precision self-positioning in indoor or outdoor complex environments.
本发明公开了一种基于多传感器融合的建筑机器人及其定位方法，属于建筑机器人技术领域，建筑机器人包括机器人本体以及设置于其上的激光雷达、双目相机、惯性测量单元和无迹卡尔曼滤波器，激光雷达用于获取周围环境的三维点云数据；双目相机用于获取周围环境的图像数据；惯性测量单元用于获取机器人本体的动态数据；无迹卡尔曼滤波器用于将三维点云数据、图像数据和动态数据转化到相同的坐标系，实时生产机器人本体的定位结果；本发明中的基于多传感器融合的建筑机器人的定位方法，通过整合激光雷达、双目相机和惯性测量单元多种传感器的优势，可使建筑机器人无论在室内还是室外复杂环境中完成高精度的自主定位。
Building robot based on multi-sensor fusion and positioning method thereof
一种基于多传感器融合的建筑机器人及其定位方法
ZHONG YIFENG (author) / WU JIAJUN (author) / JIANG SISU (author) / TANG HAO (author) / LI WEI (author) / DING PENG (author) / CHEN ZHIFU (author) / YANG XIAO (author) / ZHANG YU (author) / FAN JUN (author)
2024-09-06
Patent
Electronic Resource
Chinese
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