| 视觉和IMU融合的移动机器人运动解耦估计 |
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| 引用本文： | 路丹晖,周文晖,龚小谨,刘济林.视觉和IMU融合的移动机器人运动解耦估计[J].浙江大学学报(自然科学版 ),2012(6):1021-1026. |
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| 作者姓名： | 路丹晖 周文晖 龚小谨 刘济林 |
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| 作者单位： | 浙江大学信息与电子工程学系;杭州电子科技大学计算机学院 |
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| 基金项目： | 国家自然科学基金重大资助项目(6053407),国家自然科学基金资助项目(60902077) |
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| 摘 要： | 针对视觉里程计(VO)因累积误差导致运动姿态估计存在的偏差,提出实时扩展卡尔曼滤波器姿态估计模型,利用惯性测量单元(IMU)结合重力加速度方向作为垂直方向参考,对视觉里程计航向、俯仰和侧倾3个方向姿态估计进行解耦,修正姿态估计的累积误差;根据运动状态采用模糊逻辑调整滤波器参数,实现自适应的滤波估计,降低加速度噪声的影响.实验采用高精度的全站仪作为真值,并结合多种地形环境,实验结果表明:50m内跟踪的累积误差低于0.3m,有效地提高了视觉里程计的定位精度和鲁棒性.
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| 关 键 词： | 视觉里程计 惯性测量单元 扩展卡尔曼滤波 解耦估计 |
Decoupled mobile robot motion estimation based on fusion of visual and inertial measurement unit |
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| LU Dan-hui,ZHOU Wen-hui,GONG Xiao-jin,LIU Ji-lin.Decoupled mobile robot motion estimation based on fusion of visual and inertial measurement unit[J].Journal of Zhejiang University(Engineering Science),2012(6):1021-1026. |
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| Authors: | LU Dan-hui ZHOU Wen-hui GONG Xiao-jin LIU Ji-lin |
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| Affiliation: | 1(1.Department of Information Science and Electronic Engineering,Zhejiang University,Hangzhou 310027,China; 2.College of Computer Science,Hangzhou Dianzi University,Hangzhou 310018,China) |
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| Abstract: | Due to attitude estimation deviation caused by accumulated error in present visual odometry(VO),a real-time adaptive extended kalman filter(EKF) model was presented,with decoupled attitude estimation in yaw,pitch and roll,based on inertial measurement unit(IMU) using gravity as vertical reference to correct the accumulated error in attitude.According to the state of motion,a fuzzy logic was used to adjust filter parameters,so that adaptive filter estimation was realized.Compared with the ground truth from total station,experimental result shows that the algorithm can track motions in kinds of terrain,over distance of 50 m,with an error of less 0.3 m,effectively making VO more accurate and robust. |
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| Keywords: | visual odometry inertial measurement unit extended Kalman filter decoupled estimation |
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