人脸是人体最重要的生物特征之一，因此三维人脸建模始终是一个备受关注的研究领域。在目前大部分研究中，高精度三维人脸建模系统需要在用户配合的情况下，由专业人员操作完成，人机交互体验不佳。本论文针对这一问题，将最新的三维人脸建模算法与机器人相结合，基于机器人操作系统（Robot Operating System,ROS）开发出三维人脸数据采集和建模智能机器人，利用机器人的自动导航、人脸检测、语音交互、分布式通讯等功能实现三维人脸数据采集及建模全过程自动化。

该机器人可以自动检测行人并自动导航运动至目标人物身前，通过与目标人物进行语音交互，采集目标人物旋转头部的视频，从中提取左、中、右、下巴四张RGBD人脸图像，或根据预设三个点位直接采集目标人物左、中、右三张RGBD人脸图像，结合最新的基于RGBD的三维人脸建模算法得到高精度的三维人脸模型。同时，借助机器人的里程计信息、雷达信息准确获取采集图像对应的相机的外参数据，位姿信息，减小现有方法位姿估计的误差，同时提高三维人脸模型重建的速度。

本文开发的三维人脸数据采集和建模智能机器人在使用中展示了良好的性能，具有广泛的应用前景，可用于人脸识别、虚拟现实、医疗美容等领域。本研究为促进机器人技术与三维人脸建模的融合，推动了人工智能在人机交互领域的应用提供了有力的支持。

Human face is one of the most important biological features of human body, so 3D face modeling is always a concerned research field. In most current studies, high-precision 3D face modeling system needs to be operated and completed by professionals with the cooperation of users, resulting in poor human-computer interaction experience. Aiming at this problem, this paper combines the latest 3D face modeling algorithm with the Robot, and develops the 3D face data acquisition and modeling intelligent robot based on the Robot Operating System (ROS). Automatic navigation, pedestrian detection, voice interaction, distributed communication and other functions of the robot are used to realize the whole process automation of 3D face data acquisition and modeling.

The robot can automatically detect pedestrians and navigate to the front of the target character. Through voice interaction with the target character, it collects a video of the target character's rotating head, extracts four RGBD facial images of the left, center, right, and chin, or directly collects three RGBD facial images of the target character's left, center, and right based on preset three points, Combining the latest RGBD based 3D facial modeling algorithm to obtain high-precision 3D facial models. At the same time, by utilizing the odometer information and radar information of the robot, the external parameter data and pose information of the camera corresponding to the captured image can be accurately obtained, reducing the error of pose estimation in existing methods and improving the speed of 3D facial model reconstruction.

The intelligent robot for 3D face data acquisition and modeling developed in this paper shows good performance in use and has a wide range of application prospects, which can be used in face recognition, virtual reality, medical cosmetology and other fields. This study provides strong support for promoting the integration of robotics and 3D face modeling, and promoting the application of artificial intelligence in the field of human-computer interaction.