摘要
现阶段室内等结构化环境中的机器人定位技术备受关注,视觉-惯性传感器融合的同时定位与建图(visual-inertial simultaneous localization and mapping,VI-SLAM)系统凭借其成本低、体积小、互补性高等优点得到广泛应用。针对现有VI-SLAM系统中相机和IMU的旋转外参在线初始化困难、室内环境中的结构化特征利用不充分等问题,提出一种结构化环境下基于点线特征的双目VI-SLAM系统。该系统基于结构化环境中的线特征,采用先静止、后运动的两步法,在线初始化相机和IMU之间的旋转外参,并通过融合视觉提供的点、线特征的重投影误差约束和IMU提供的预积分约束,共同优化定位系统的状态量。在EuRoC室内无人机数据集和真实地下停车场中的试验表明,两步初始化旋转外参算法有效且准确,可为优化环节提供良好的初始值,通过与多种视觉定位算法进行对比,验证了该系统拥有更高的定位精度。
Robot localization technology in structured environments such as indoor has attracted much attention at present.The visual-inertial simultaneous localization and mapping(VI-SLAM)system has been widely used with its low-cost,small-size and high-complementarity.A stereo VI-SLAM system based on point-line features in structured environment is proposed to overcome the difficulty in camera-IMU extrinsic online calibration and insufficient utilization of structured features in the existing VI-SLAM system.Based on the line features in the structured environment,the system uses a two-step method of first stationary and then moving to online initialize the camera-IMU extrinsic parameters,and jointly optimizes the state variables of the localization system by fusing the re-projection error constraints of the point-line features provided by vision and the pre-integration constraints provided by IMU.Experiments on EuRoC indoor UAV datasets and real underground parking lot show that the two-step initialization extrinsic parameters algorithm is effective and accurate to provide good initial value for optimization.Compared with other localization algorithms,the system has higher localization accuracy.
作者
郭翼彪
周云水
黄圣杰
刘硕
谢国涛
秦晓辉
GUO Yibiao;ZHOU Yunshui;HUANG Shengjie;LIU Shuo;XIE Guotao;QIN Xiaohui(College of Mechanical and Vehicle Engineering,Hunan University,Changsha 410082;Wuxi Intelligent Control of Research Institute(WICRI)of Hunan University,Wuxi 214072)
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2024年第6期296-305,共10页
Journal of Mechanical Engineering
基金
国家自然科学基金(52102456,52172384)
长沙市自然科学基金(kq2202162)
汽车车身先进设计制造国家重点实验室开放课题(32115013)资助项目。
