SMITH R C , CHEESEMAN P . On the representation and estimation of spatial uncertainty [J ] . The International Journal of Robotics Research , 1986 , 5 ( 4 ): 56 - 68 . DOI: 10.1177/027836498600500404 http://doi.org/10.1177/027836498600500404 http://journals.sagepub.com/doi/10.1177/027836498600500404 http://journals.sagepub.com/doi/10.1177/027836498600500404 This paper describes a general method for estimating the nominal relationship and expected error (covariance) between coordinate frames representing the relative locations of ob jects. The frames may be known only indirectly through a series of spatial relationships, each with its associated error, arising from diverse causes, including positioning errors, measurement errors, or tolerances in part dimensions. This estimation method can be used to answer such questions as whether a camera attached to a robot is likely to have a particular reference object in its field of view. The calculated estimates agree well with those from an independent Monte Carlo simulation. The method makes it possible to decide in advance whether an uncertain relationship is known accu rately enough for some task and, if not, how much of an improvement in locational knowledge a proposed sensor will provide. The method presented can be generalized to six degrees offreedom and provides a practical means of esti mating the relationships ( position and orientation) among objects, as well as estimating the uncertainty associated with the relationships.

刘全攀 , 王正杰 , 王寰 . 基于双目视觉-惯性导航的轻型无人机导航算法 [J ] . 兵工学报 , 2020 , 41 ( 增刊2 ): 242 - 248 .

LIU Q P , WANG Z J , WANG H . Navigation algorithm of light UAV based on stereo visual inertial navigation odometer [J ] . Acta Armamentarii , 2020 , 41 ( S2 ): 242 - 248 . (in Chinese)

王金科 , 左星星 , 赵祥瑞 , 等 . 多源融合SLAM的现状与挑战 [J ] . 中国图象图形学报 , 2022 , 27 ( 2 ): 368 - 389 .

WANG J K , ZUO X X , ZHAO X R , et al . Review of multi-source fusion SLAM: current status and challenges [J ] . Journal of Image and Graphics , 2022 , 27 ( 2 ): 368 - 389 . (in Chinese)

STURZL W . A lightweight single-camera polarization compass with covariance estimation [C ] //Proceedings of IEEE International Conference on Computer Vision. Venice , Italy : IEEE , 2017 : 5353 - 5361 .

LIU Z Y , ZHANG Q , PAN M C , et al . Magnetic disturbance field compensation of a geomagnetic vector measuring instrument [J ] . IEEJ Transactions on Electrical and Electronics Engineering , 2018 , 13 ( 3 ): 356 - 361 . DOI: 10.1002/tee.2018.13.issue-3 http://doi.org/10.1002/tee.2018.13.issue-3 https://onlinelibrary.wiley.com/toc/19314981/13/3 https://onlinelibrary.wiley.com/toc/19314981/13/3

常宜峰 , 种洋 , 柴洪洲 , 等 . 世界地磁场模型精度评价 [J ] . 武汉大学学报(信息科学版) , 2016 , 41 ( 10 ): 1398 - 1403 .

CHANG Y F , CHONG Y , CHAI H Z , et al . Evaluation of world magnetic model accuracy [J ] . Geomatics and Information Science of Wuhan University , 2016 , 41 ( 10 ): 1398 - 1403 . (in Chinese)

CAMPOS C , ELVIRA R , RODRIGUEZ J J G , et al . ORB-SLAM3: An accurate open-source library for visual, visual-inertial, and multi-map SLAM [J ] . IEEE Transactions on Robotics , 2021 , 37 ( 6 ): 1874 - 1890 . DOI: 10.1109/TRO.2021.3075644 http://doi.org/10.1109/TRO.2021.3075644 https://ieeexplore.ieee.org/document/9440682/ https://ieeexplore.ieee.org/document/9440682/

ENGEL J , SCHOPS T , CREMERS D . LSD-SLAM: Large-scale direct monocular SLAM [C ] //Proceedings of European Conference on Computer Vision. Zurich , Switzerland : Springer , 2014 : 834 - 849 .

ENGEL J , KOLTUN V , CREMERS D . Direct sparse odometry [J ] . IEEE Transactions on Pattern Analysis and Machine Intelligence , 2018 , 40 ( 3 ): 611 - 625 . DOI: 10.1109/TPAMI.2017.2658577 http://doi.org/10.1109/TPAMI.2017.2658577 Direct Sparse Odometry (DSO) is a visual odometry method based on a novel, highly accurate sparse and direct structure and motion formulation. It combines a fully direct probabilistic model (minimizing a photometric error) with consistent, joint optimization of all model parameters, including geometry-represented as inverse depth in a reference frame-and camera motion. This is achieved in real time by omitting the smoothness prior used in other direct methods and instead sampling pixels evenly throughout the images. Since our method does not depend on keypoint detectors or descriptors, it can naturally sample pixels from across all image regions that have intensity gradient, including edges or smooth intensity variations on essentially featureless walls. The proposed model integrates a full photometric calibration, accounting for exposure time, lens vignetting, and non-linear response functions. We thoroughly evaluate our method on three different datasets comprising several hours of video. The experiments show that the presented approach significantly outperforms state-of-the-art direct and indirect methods in a variety of real-world settings, both in terms of tracking accuracy and robustness.

GAO X , WANG R , DEMMEL N , et al . LDSO: Direct sparse odometry with loop closure [C ] //Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. Madrid, Spain:IEEE , 2018 : 2198 - 2204 .

ZUBIZARRETA J , AGUINAGA I , MONTIEL J M M . Direct sparse mapping [J ] . IEEE Transactions on Robotics , 2020 , 36 ( 4 ): 1363 - 1370 . DOI: 10.1109/TRO.8860 http://doi.org/10.1109/TRO.8860 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8860 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8860

夏琳琳 , 蒙跃 , 王策 , 等 . 基于Retinex理论的稀疏直接法VSLAM三维重建 [J ] . 中国惯性技术学报 , 2021 , 29 ( 2 ): 147 - 153 .

XIA L L , MENG Y , WANG C , et al . Retinex-based sparse direct VSLAM 3D reconstruction [J ] . Journal of Chinese Inertial Technology , 2021 , 29 ( 2 ): 147 - 153 . (in Chinese)

XIA L L , CUI J S , SHEN R , et al . A survey of image semantics-based visual simultaneous localization and mapping: application-oriented solutions to antonymous navigation of mobile robots [J ] . International Journal of Advanced Robotic Systems , 2020 , 17 ( 3 ): 1 - 17 .

刘忠泽 , 陈慧岩 , 崔星 , 等 . 无人平台越野环境下同步定位与地图创建 [J ] . 兵工学报 , 2019 , 40 ( 12 ): 2399 - 2406 . DOI: 10.3969/j.issn.1000-1093.2019.12.002 http://doi.org/10.3969/j.issn.1000-1093.2019.12.002 为了满足无人平台在越野环境下碰撞检测以及定位的需求、解决三维点云地图处理计算资源耗费大的问题，设计一种适用于越野环境的同步定位与地图创建方案。提出一种拓扑层次地图，将整个地图划分为多个具有层级结构的三维体素子地图，并以概率方法表示每个体素的状态，进而提取可通行区域。基于三维激光雷达和惯性测量单元，提出一种基于分支定界法的旋转直方图最近邻匹配实时闭环检测方法，并使用Ceres优化稀疏位姿图实现6自由度全局位姿实时优化。越野环境下的实验结果显示：该地图的创建以及可通行区域的提取效果良好，全局定位误差在1 m以内，姿态基本与参考高精度惯性导航系统保持一致；基于该方案提取的可通行区域以及位姿优化结果可满足无人平台实时运动的需求。

LIU Z Z , CHEN H Y , CUI X , et al . Real-time LiDAR SLAM in off-road environment for UGV [J ] . Acta Armamentarii , 2019 , 40 ( 12 ): 2399 - 2406 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2019.12.002 http://doi.org/10.3969/j.issn.1000-1093.2019.12.002 Simultaneous localization and mapping (SLAM) plays a more and more important role in the environment perception system of unmanned ground vehicle (UGV). A hierarchical global topological map is proposed to solve the low real time capability problem during processing of 3D lidar point cloud map, which divides the entire map into many submaps consisting of large numbers of tree-structure-based voxels, and the submaps are organized with the help of topology. The probabilistic methods are used to represent the state of each voxel being occupied/null. A transitable area is extracted based on the submaps for the UGV's path planning. With the help of an inertial measurement unit (IMU) and two 3D lidars, a branch and bound search (BBS)-based loop detection algorithm called RHM-ICP algorithm is proposed to realize a real time 6-degrees-of-freedom global pose optimization with the help of Ceres, which is to process the sparse pose adjustment (SPA). Experimental results obtained from a real large-scale off-road environment shows an effective reduction of lidar odometry pose accumulative error with a global location error of less than 1 m and a good performance of 3D mapping. Key

龙霄潇 , 程新景 , 朱昊 , 等 . 三维视觉前沿进展 [J ] . 中国图象图形学报 , 2021 , 26 ( 6 ): 1389 - 1428 .

LONG X X , CHENG X J , ZHU H , et al . Recent progress in 3D vision [J ] . Journal of Image and Graphics , 2021 , 26 ( 6 ): 1389 - 1428 . (in Chinese)

WEISS S , SIEGWART R . Real-time metric state estimation for modular vision-inertial systems [C ] //Proceedings of IEEE International Conference on Robotics and Automation. Shanghai , China : IEEE , 2011 : 4531 - 4537 .

MOURIKIS A I , ROUMELIOTIS S I . A multi-state constraint Kalman filter for vision-aided inertial navigation [C ] //Proceedings of IEEE International Conference on Robotics and Automation . Rome, Italy : IEEE , 2007 : 3565 - 3572 .

BLOESCH M , OMARI S , HUTTER M , et al . Robust visual inertial odometry using a direct EKF-based approach [C ] //Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. Hamburg , Germany : IEEE , 2015 : 298 - 304 .

LEUTENEGGER S , LYNEN S , BOSSE M , et al . Keyframe-based visua-inertial odometry using nonlinear optimization [J ] . The International Journal of Robotics Research , 2014 , 34 ( 3 ): 314 - 334 . DOI: 10.1177/0278364914554813 http://doi.org/10.1177/0278364914554813 http://journals.sagepub.com/doi/10.1177/0278364914554813 http://journals.sagepub.com/doi/10.1177/0278364914554813 Combining visual and inertial measurements has become popular in mobile robotics, since the two sensing modalities offer complementary characteristics that make them the ideal choice for accurate visual–inertial odometry or simultaneous localization and mapping (SLAM). While historically the problem has been addressed with filtering, advancements in visual estimation suggest that nonlinear optimization offers superior accuracy, while still tractable in complexity thanks to the sparsity of the underlying problem. Taking inspiration from these findings, we formulate a rigorously probabilistic cost function that combines reprojection errors of landmarks and inertial terms. The problem is kept tractable and thus ensuring real-time operation by limiting the optimization to a bounded window of keyframes through marginalization. Keyframes may be spaced in time by arbitrary intervals, while still related by linearized inertial terms. We present evaluation results on complementary datasets recorded with our custom-built stereo visual–inertial hardware that accurately synchronizes accelerometer and gyroscope measurements with imagery. A comparison of both a stereo and monocular version of our algorithm with and without online extrinsics estimation is shown with respect to ground truth. Furthermore, we compare the performance to an implementation of a state-of-the-art stochastic cloning sliding-window filter. This competitive reference implementation performs tightly coupled filtering-based visual–inertial odometry. While our approach declaredly demands more computation, we show its superior performance in terms of accuracy.

QIN T , LI P L , SHEN S J . VINS-Mono: a robust and versatile monocular visual-inertial state estimator [J ] . IEEE Transactions on Robotics , 2018 , 34 ( 4 ): 1004 - 1020 . DOI: 10.1109/TRO.8860 http://doi.org/10.1109/TRO.8860 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8860 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8860

LI P L , QIN T , HU B T , et al . Monocular visual-inertial state estimation for mobile augmented reality [C ] //Proceedings of IEEE International Symposium on Mixed and Augmented Reality. Nantes , France : IEEE , 2017 : 11 - 21 .

QIN T , PAN J , CAO S Z , et al . A general optimization-based framework for local odometry estimation with multiple sensors:arXiv:1901.03638 [R/OL ] . Ithaca, NY , US : Cornell University , 2019 . (2019-01-11). https://arxiv.org/abs/1901.03638 https://arxiv.org/abs/1901.03638 https://arxiv.org/abs/1901.03638

曹力科 , 肖晓辉 . 基于卷帘快门RGB-D相机的视觉惯性SLAM方法 [J ] . 机器人 , 2021 , 43 ( 2 ): 193 - 202 . DOI: 10.13973/j.cnki.robot.200245 http://doi.org/10.13973/j.cnki.robot.200245 针对当前单目视觉惯性SLAM（同步定位与地图创建）中初始化需要加速度激励以及高IMU（惯性测量单元）噪声条件下系统精度下降的问题，提出一种基于卷帘快门RGB-D相机的视觉惯性SLAM方法——VINS-RSD方法．VINS-RSD方法联合卷帘快门RGB-D图像和IMU对系统进行初始化，通过控制特征的速度对卷帘快门效应进行校正，并采用一种带置信因子的损失核函数进行滑动窗口优化．为了评测该方法，在WHU-RSVI数据集的基础上制作了一个可以评价RGB-D视觉惯性SLAM算法的开源深度数据集并进行实验验证．结果表明，与VINS-Mono方法相比，VINS-RSD方法的均方根误差平均值下降了30.76%，表明该方法能获得更高的跟踪精度．

CAO L K , XIAO X H . A visual-inertial SLAM method based on rolling shutter RGB-D cameras [J ] . Robot , 2021 , 43 ( 2 ): 193 - 202 . (in Chinese) DOI: 10.13973/j.cnki.robot.200245 http://doi.org/10.13973/j.cnki.robot.200245 For the current monocular visual-inertial SLAM (simultaneous localization and mapping) systems, the acceleration excitation is necessary, and the system accuracy will decrease in the case of high IMU (inertial measurement unit) noises. To solve those problems, a visual-inertial SLAM method based on rolling shutter RGB-D cameras is proposed, named VINS-RSD method, which combines rolling shutter RGB-D image and IMU to initialize the system. The rolling shutter effect is corrected by controlling the feature velocity, and a loss kernel function with confidence factor is applied to the sliding window optimization. An open-source depth dataset extended from WHU-RSVI dataset is developed to evaluate the RGB-D visual-inertial SLAM method. Experiments are performed on the dataset and the root mean square error of VINS-RSD method is reduced by 30.76% compared to VINS-Mono (monocular visual-inertial system) method, which demonstrates that the proposed method can achieve a higher tracking accuracy.

WEN S H , LIU X , ZHANG H , et al . Dense point cloud map construction based on stereo VINS for mobile vehicles [J ] . ISPRS Journal of Photogrammetry and Remote Sensing , 2021 , 178 : 328 - 344 . DOI: 10.1016/j.isprsjprs.2021.06.009 http://doi.org/10.1016/j.isprsjprs.2021.06.009 https://linkinghub.elsevier.com/retrieve/pii/S0924271621001672 https://linkinghub.elsevier.com/retrieve/pii/S0924271621001672

LIU T A , LIN H Y , LIN W Y . InertialNet: Toward robust SLAM via visual inertial measurement [C ] //Proceedings of IEEE Intelligent Transportation Systems Conference . Auckland, New Zealand : IEEE , 2019 : 1311 - 1316 .

KIM Y , YOON S , KIM S , et al . Unsupervised balanced covariance learning for visual-inertial sensor fusion [J ] . IEEE Robotics and Automation Letters , 2021 , 6 ( 2 ): 819 - 826 . DOI: 10.1109/LSP.2016. http://doi.org/10.1109/LSP.2016. https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7083369 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7083369

FU Q , WANG J L , YU H S , et al . PL-VINS: real-time monocular visual-inertial SLAM with point and line: ArXiv:2009.07462 [R/OL ] . Ithaca, NY , US : Cornell University , 2020 (2020-9-16). https://arxiv.org/abs/2009.07462. https://arxiv.org/abs/2009.07462 https://arxiv.org/abs/2009.07462

ZHANG J , KAESS M , SINGH S . Real-time depth enhanced monocular odometry [C ] //Proceedings of 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. Chicago, IL , US : IEEE , 2014 : 4973 - 4980 .

CAMURRI M , RAMEZANI M , NOBILI S , et al . Pronto: a multi-sensor state estimator for legged robots in real world scenarios [J ] . Frontiers in Robotics and AI , 2020 , 7 : 68 . DOI: 10.3389/frobt.2020.00068 http://doi.org/10.3389/frobt.2020.00068 https://www.frontiersin.org/article/10.3389/frobt.2020.00068/full https://www.frontiersin.org/article/10.3389/frobt.2020.00068/full

SHAO W Z , VIJAYARANGAN S , LI C , et al . Stereo visual inertial LiDAR simultaneous localization and mapping [C ] //Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. Macau , China : IEEE , 2019 : 370 - 377 .

SHAN T X , ENGLOT B , RATTI C , et al . LVI-SAM: tightly-coupled lidar-visual-inertial odometry via smoothing and mapping [C ] //Proceedings of IEEE International Conference on Robotics and Automation. Xi’an , China : IEEE , 2021 : 5692 - 5698 .

WISTH D , CAMURRI M , DAS S , et al . Unified multi-modal landmark tracking for tightly coupled lidar-visual-inertial odometry [J ] . IEEE Robotics and Automation Letters , 2021 , 6 ( 2 ): 1004 - 1011 . DOI: 10.1109/LSP.2016. http://doi.org/10.1109/LSP.2016. https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7083369 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7083369

LEE W , ECKENHOFF K , GENEVA P , et al . Intermittent GPS-aided VIO: online initialization and calibration [C ] //Proceedings of IEEE International Conference on Robotics and Automation. Paris , France : IEEE , 2020 : 5724 - 5731 .

CAO S Z , LU X Y , SHEN S J . GVINS: tightly coupled GNSS-visual-inertial fusion for smooth and consistent state estimation [J ] . IEEE Transactions on Robotics , 2022 , 38 ( 4 ): 2004 - 2021 . DOI: 10.1109/TRO.2021.3133730 http://doi.org/10.1109/TRO.2021.3133730 https://ieeexplore.ieee.org/document/9667780/ https://ieeexplore.ieee.org/document/9667780/

YODER J E , IANNUCCI P A , NARULA L , et al . Multi-antenna vision-and-inertial-aided CDGNSS for micro aerial vehicle pose estimation [C ] //Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation. Manassas, VA , US : The Institute of Navigation , 2020 : 2281 - 2298 .

LI T , ZHANG H P , GAO Z Z , et al . Tight fusion of a monocular camera, MEMS-IMU, and single-frequency multi-GNSS RTK for precise navigation in GNSS-challenged environments [J ] . Remote Sensing , 2019 , 11 ( 6 ): 610 . DOI: 10.3390/rs11060610 http://doi.org/10.3390/rs11060610 https://www.mdpi.com/2072-4292/11/6/610 https://www.mdpi.com/2072-4292/11/6/610 Precise position, velocity, and attitude is essential for self-driving cars and unmanned aerial vehicles (UAVs). The integration of global navigation satellite system (GNSS) real-time kinematics (RTK) and inertial measurement units (IMUs) is able to provide high-accuracy navigation solutions in open-sky conditions, but the accuracy will be degraded severely in GNSS-challenged environments, especially integrated with the low-cost microelectromechanical system (MEMS) IMUs. In order to navigate in GNSS-denied environments, the visual–inertial system has been widely adopted due to its complementary characteristics, but it suffers from error accumulation. In this contribution, we tightly integrate the raw measurements from the single-frequency multi-GNSS RTK, MEMS-IMU, and monocular camera through the extended Kalman filter (EKF) to enhance the navigation performance in terms of accuracy, continuity, and availability. The visual measurement model from the well-known multistate constraint Kalman filter (MSCKF) is combined with the double-differenced GNSS measurement model to update the integration filter. A field vehicular experiment was carried out in GNSS-challenged environments to evaluate the performance of the proposed algorithm. Results indicate that both multi-GNSS and vision contribute significantly to the centimeter-level positioning availability in GNSS-challenged environments. Meanwhile, the velocity and attitude accuracy can be greatly improved by using the tightly-coupled multi-GNSS RTK/INS/Vision integration, especially for the yaw angle.

WANG J Z , LI L L , YU H , et al . VIMO: avisual-inertial-magnetic navigation system based on non-linear optimizations [J ] . Sensors , 2020 , 20 ( 16 ): 4386 . DOI: 10.3390/s20164386 http://doi.org/10.3390/s20164386 https://www.mdpi.com/1424-8220/20/16/4386 https://www.mdpi.com/1424-8220/20/16/4386 Visual-inertial navigation systems are credited with superiority over both pure visual approaches and filtering ones. In spite of the high precision many state-of-the-art schemes have attained, yaw remains unobservable in those systems all the same. More accurate yaw estimation not only means more accurate attitude calculation but also leads to better position estimation. This paper presents a novel scheme that combines visual and inertial measurements as well as magnetic information for suppressing deviation in yaw. A novel method for initializing visual-inertial-magnetic odometers, which recovers the directions of magnetic north and gravity, the visual scalar factor, inertial measurement unit (IMU) biases etc., has been conceived, implemented, and validated. Based on non-linear optimization, a magnetometer cost function is incorporated into the overall optimization objective function as a yawing constraint among others. We have done extensive research and collected several datasets recorded in large-scale outdoor environments to certify the proposed system’s viability, robustness, and performance. Cogent experiments and quantitative comparisons corroborate the merits of the proposed scheme and the desired effect of the involvement of magnetic information on the overall performance.

LIU S Q , LI M H , LIN R , et al . Tightly coupled algorithm of visual inertial odometry and magnetometer fusion [C ] //Proceedings of IEEE 5th Information Technology and Mechatronics Engineering Conference . Chongqing, China : IEEE , 2020 : 330 - 335 .

HASHEMIFAR Z S , ADHIVARAHAN C , BALAKRISHNAN A , et al . Augmenting visual SLAM with Wi-Fi sensing for indoor applications [J ] . Autonomous Robots , 2019 , 43 ( 8 ): 2245 - 2260 . DOI: 10.1007/s10514-019-09874-z http://doi.org/10.1007/s10514-019-09874-z Recent trends have accelerated the development of spatial applications on mobile devices and robots. These include navigation, augmented reality, human-robot interaction, and others. A key enabling technology for such applications is the understanding of the device's location and the map of the surrounding environment. This generic problem, referred to as Simultaneous Localization and Mapping (SLAM), is an extensively researched topic in robotics. However, visual SLAM algorithms face several challenges including perceptual aliasing and high computational cost. These challenges affect the accuracy, efficiency, and viability of visual SLAM algorithms, especially for long-term SLAM, and their use in resource-constrained mobile devices. A parallel trend is the ubiquity of Wi-Fi routers for quick Internet access in most urban environments. Most robots and mobile devices are equipped with a Wi-Fi radio as well. We propose a method to utilize Wi-Fi received signal strength to alleviate the challenges faced by visual SLAM algorithms. To demonstrate the utility of this idea, this work makes the following contributions: (i) We propose a generic way to integrate Wi-Fi sensing into visual SLAM algorithms, (ii) We integrate such sensing into three well-known SLAM algorithms, (iii) Using four distinct datasets, we demonstrate the performance of such augmentation in comparison to the original visual algorithms and (iv) We compare our work to Wi-Fi augmented FABMAP algorithm. Overall, we show that our approach can improve the accuracy of visual SLAM algorithms by 11% on average and reduce computation time on average by 15% to 25%.

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ZHAO H J , XU W J , ZHANG Y , et al . Polarization patterns under different sky conditions and a navigation method based on the symmetry of the AOP map of skylight [J ] . Optics Express , 2018 , 26 ( 22 ): 28589 - 28603 . DOI: 10.1364/OE.26.028589 http://doi.org/10.1364/OE.26.028589 The polarization states of a skylight can be used for navigation by a lot of insects as well as by human beings. However, the polarization patterns of skylight are greatly influenced by the atmospheric conditions. This paper studied the polarization patterns of skylight under different sky conditions by polarized imaging measurements, in which the AOT (Aerosol Optical Thickness) and clouds were taken into account. The results showed that both the aerosol and cloud disturbed the polarization patterns of the skylight, but the patterns of AOP (Angle of Polarization) showed great robustness. The symmetry of the AOP images was found to be quite steady under most of the sky conditions. We proposed a navigation method by finding out the solar meridian according to the symmetry of an AOP map. The results showed that the solar meridian can be identified accurately under different situations. The calculation errors slightly fluctuated along with the aerosol and cloud.

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LAMBRINOS D , KOBAYASHI H , PFEIFER R , et al . An autonomous agent navigating with a polarized light compass [J ] . Adaptive Behavior , 1997 , 6 ( 1 ): 131 - 161 . DOI: 10.1177/105971239700600104 http://doi.org/10.1177/105971239700600104 http://journals.sagepub.com/doi/10.1177/105971239700600104 http://journals.sagepub.com/doi/10.1177/105971239700600104 One of the fundamental abilities required in autonomous agents is homing. Natural agents—for instance, desert ants—solve the homing problem mainly by using path integration within an egocentric frame of reference. When employing such a mechanism, compass information for determining direction is necessary, and the precision of the compass will have a crucial effect on the precision of homing. For deriving compass information, certain insects use the pattern of polarized light in the sky that arises due to scattering of sunlight in the atmosphere (polarized light compass). The analysis of skylight polarization is mediated by specialized photoreceptors and neurons in the visual system. Inspired by the insect's polarized light compass, we have constructed a polarization compass that was employed successfully on the mobile robot Sahabot. Three models for extracting compass information from the polarization pattern of the sky were tested. In this article, we describe the navigation system and report results of experiments performed with the Sahabot in one of the natural habitats of the desert ant Cataglyphis in North Africa.

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田柳 , 高隽 , 范之国 , 等 . 基于大气偏振模式分布规律的导航方向角计算方法 [J ] . 电子学报 , 2012 , 40 ( 1 ): 141 - 146 . DOI: 10.3969/j.issn.0372-2112.2012.01.023 http://doi.org/10.3969/j.issn.0372-2112.2012.01.023 针对已有仿生偏振光导航方法中,根据局部天空区域的偏振信息获取导航信息存在的缺陷,提出一种基于大气偏振模式分布规律的导航方向角计算方法.该方法利用大气偏振模式的对称性定义了偏振响应和函数,根据大气偏振模式有限采样点的偏振信息,拟合估计出太阳子午线位置,并最终获取导航方向角信息,最后通过多组观测时刻、多组观测地点的仿真实验,验证了基于大气偏振模式分布规律的导航方向角计算方法的有效性.

TIAN L , GAO J , FAN Z G , et al . The method of the navigation direction angle calculation with the distribution of the atmospheric polarization pattern [J ] . Acta Electronica Sinica , 2012 , 40 ( 1 ): 141 - 146 . (in Chinese) DOI: 10.3969/j.issn.0372-2112.2012.01.023 http://doi.org/10.3969/j.issn.0372-2112.2012.01.023 For the disadvantages of the existing method of bionic polarization navigation,that calculates the navigation direction angle based on the polarization information of the local sky region,a method is proposed to calculate the navigation direction angle based on the symmetrical distribution of the atmospheric polarization mode.The function of polarization response sum is defined according to the symmetry of the atmosphere polarization mode,a finite number of sampling points of the atmospheric polarization are acquired to calculate the position of the solar meridian and to determine the navigation direction angle.The corresponding validation experiment is also given to test the method of navigation direction angle calculation using the symmetry of the atmospheric polarization distribution mode.

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褚金奎 , 关乐 , 李世奇 , 等 . 大气偏振模式图分布及仿生偏振导航技术 [J ] . 遥感学报 , 2018 , 22 ( 6 ): 969 - 679 .

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KONG X L , WU W Q , ZHANG L L , et al . Performance improvement of visual-inertial navigation system by using polarized light compass [J ] . Industrial Robot—The International Journal of Robotics Research and Application , 2016 , 43 ( 6 ): 588 - 595 . DOI: 10.1108/IR-03-2016-0103 http://doi.org/10.1108/IR-03-2016-0103 https://www.emerald.com/insight/content/doi/10.1108/IR-03-2016-0103/full/html https://www.emerald.com/insight/content/doi/10.1108/IR-03-2016-0103/full/html This paper aims to present a method for improving the performance of the visual-inertial navigation system (VINS) by using a bio-inspired polarized light compass.

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ZHOU W Z , FAN C , HE X F , et al . Integrated bionic polarized vision/VINS for goal-directed navigation and homing in unmanned ground vehicle [J ] . IEEE Sensors Journal , 2021 , 21 ( 10 ): 11232 - 11241 . DOI: 10.1109/JSEN.2021.3066844 http://doi.org/10.1109/JSEN.2021.3066844 https://ieeexplore.ieee.org/document/9380405/ https://ieeexplore.ieee.org/document/9380405/

XIA L L , LIU R M , ZHANG D C , et al . Polarized light-aided visual-inertial navigation system: global heading measurements and graph optimization based multi-sensor fusion [J ] . Measurement Science and Technology , 2022 , 33 ( 5 ): 055111 . DOI: 10.1088/1361-6501/ac4637 http://doi.org/10.1088/1361-6501/ac4637 Polarized skylight is as fundamental a constituent of passive navigation as the geomagnetic field. With regard to its applicability to outdoor robot localization, a polarized light-aided visual-inertial navigation system (VINS) modelization dedicated to globally optimized pose estimation and heading correction is constructed. The combined system follows typical visual simultaneous localization and mapping (SLAM) frameworks, and we propose a methodology to fuse global heading measurements with visual and inertial information in a graph optimization-based estimator. With ideas of‘adding new attributes of graph vertices and creating heading error-encoded constraint edges’, the heading, as the absolute orientation reference, is estimated by the Berry polarization model and continuously updated in a graph structure. The formulized graph optimization process for multi-sensor fusion is simultaneously provided. In terms of campus road experiments on the Bulldog-CX robot platform, the results are compared against purely stereo camera-dependent and VINS Fusion frameworks, revealing that our design is substantially more accurate than others with both locally and globally consistent position and attitude estimates. As a passive and tightly coupled navigation mode, the polarized light-aided VINS can therefore be considered as a tool candidate for a class of visual SLAM-based multi-sensor fusion.

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褚金奎 , 陈建华 , 李金山 , 等 . 一种偏振光/双目视觉仿生组合导航方法 [J ] . 光子学报 , 2021 , 50 ( 5 ): 192 - 201 .

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褚金奎 , 武进 , 李金山 , 等 . 偏振光传感器在四旋翼飞行器中的应用 [J ] . 电子学报 , 2020 , 48 ( 1 ): 198 - 203 . DOI: 10.3969/j.issn.0372-2112.2020.01.024 http://doi.org/10.3969/j.issn.0372-2112.2020.01.024 为了实现偏振光传感器在实际三维空间中的导航应用，设计了一种基于仿生偏振光导航传感器、微惯性测量单元（MIMU）与全球定位系统（GPS）的组合导航控制系统，并实际应用到了四旋翼导航控制之中.本文首先介绍了偏振光传感器的功能模型和测角原理.其次采用扩展卡尔曼滤波（EKF）技术设计了偏振光传感器、MIMU、GPS的信息融合算法，通过室外飞行试验对该导航系统的性能进行了测试，并与传统MIMU/GPS/电子罗盘导航系统进行了比较.结果显示：在有磁场干扰环境下，基于偏振光的导航控制系统平均位置精度较传统导航系统提高了50.4%.实验结果表明：该导航控制系统实时性好、精度较高、抗电磁干扰能力强，且误差不随时间累积，基本满足移动载体进行自主导航时的精度和可靠性要求.

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