摘要
针对动态物体对同时定位与建图(SLAM)的影响,基于双目直接法,提出一种动态场景下的语义分割双目惯性SLAM方法.前端采用自适应光流法识别并滤除运动特征点.在粗跟踪阶段,融合去除动态物体后的静态双目残差与惯性测量单元(IMU)信息,校正视觉位姿,提升双目直接法里程计的精度和鲁棒性.后端基于滑动窗口紧耦合双目与IMU数据,引入跨帧双向特征投影方法,构建主导帧左目到目标帧右目的投影残差,确保动态特征较多时的位姿估计稳定.在KITTI及自制数据集上验证,改进的动态检测有效滤除了动态特征.相比双目直接法SLAM,平移精度和旋转精度分别提升23.89%和20.18%,自制数据集轨迹误差降低33.14%.
A semantic segmentation-based stereo inertial simultaneous localization and mapping(SLAM)method is proposed for dynamic scenes to address the impact of dynamic objects on SLAM using a stereo direct method.The frontend employs adaptive optical flow thresholding for dynamic feature recognition,filtering out truly moving features to enhance localization accuracy in dynamic environments.During coarse tracking,it fuses static stereo residual constraints(after dynamic object removal)with inertial measurement unit data to correct the visual pose,addressing the low accuracy and poor robustness of stereo direct visual odometry.For backend optimization,a sliding window approach tightly couples stereo and inertial measurement unit(IMU)data.A novel cross-frame bidirec-tional feature projection method constructs projection residuals from the host frame′s left image to the target frame′s right image,ensuring stable pose estimation even in scenes with abundant dynamic features.Evaluations on the KITTI dataset and a custom dataset demonstrate that the improved dynamic detection effectively filters dynamic features.Compared to stereo direct SLAM,the proposed method achieves improvements of 23.89% in translational accuracy and 20.18% in rotational accuracy,while reducing the root mean square error of the motion trajectory by 33.14% on the custom dataset.
作者
林申炀
彭育辉
孙宝哲
张淦
张家铭
LIN Shenyang;PENG Yuhui;SUN Baozhe;ZHANG Gan;ZHANG Jiaming(School of Mechanical Engineering and Automation,Fuzhou University,Fuzhou,Fujian 350108,China)
出处
《福州大学学报(自然科学版)》
北大核心
2026年第2期154-161,共8页
Journal of Fuzhou University(Natural Science Edition)
基金
福建省科技厅引导性基金资助项目(2022H0007)。
关键词
动态环境
光流法
双目直接法
IMU融合
dynamic environment
optical flow method
stereo direct method
IMU fusion
