Sawano, H.[Hiroaki],
Okada, M.[Minoru],
A Road Extraction Method by an Active Contour Model with Inertia and
Differential Features,
IEICE(E89-D), No. 7, July 2006, pp. 2257-2267.
DOI Link
0607
BibRef
Ramanandan, A.,
Chen, A.,
Farrell, J.A.,
Inertial Navigation Aiding by Stationary Updates,
ITS(13), No. 1, March 2012, pp. 235-248.
IEEE DOI
1203
BibRef
Alam, N.,
Kealy, A.,
Dempster, A.G.,
Cooperative Inertial Navigation for GNSS-Challenged Vehicular
Environments,
ITS(14), No. 3, 2013, pp. 1370-1379.
IEEE DOI
1309
Carrier frequency offset (CFO)
BibRef
Guan, T.[Tao],
He, Y.F.[Yun-Feng],
Gao, J.[Juan],
Yang, J.Z.[Jian-Zhong],
Yu, J.Q.[Jun-Qing],
On-Device Mobile Visual Location Recognition by Integrating Vision
and Inertial Sensors,
MultMed(15), No. 7, 2013, pp. 1688-1699.
IEEE DOI
1312
computer vision
BibRef
Schlichting, A.[Alexander],
Brenner, C.[Claus],
Schon, S.[Steffen],
Evaluation of inertial measurement systems using laser scanners and
known landmarks,
PFG(2014), No. 1, February 2014, pp. 5-15.
DOI Link
1405
BibRef
Chiang, K.W.[Kai-Wei],
Lin, C.A.[Cheng-An],
Duong, T.T.[Thanh-Trung],
The Performance Analysis of the Tactical Inertial Navigator Aided by
Non-GPS Derived References,
RS(6), No. 12, 2014, pp. 12511-12526.
DOI Link
1412
BibRef
Asadi, E.[Ehsan],
Bottasso, C.L.[Carlo L.],
Delayed fusion for real-time vision-aided inertial navigation,
RealTimeIP(10), No. 4, December 2015, pp. 633-646.
Springer DOI
1512
BibRef
Mousa, M.,
Sharma, K.,
Claudel, C.G.,
Inertial Measurement Units-Based Probe Vehicles: Automatic
Calibration, Trajectory Estimation, and Context Detection,
ITS(19), No. 10, October 2018, pp. 3133-3143.
IEEE DOI
1810
Global Positioning System, Sensors, Trajectory, Probes,
Wireless sensor networks, Urban areas, Accelerometers,
inertial navigation
BibRef
Abolfazli Esfahani, M.,
Wang, H.,
Wu, K.,
Yuan, S.,
AbolDeepIO: A Novel Deep Inertial Odometry Network for Autonomous
Vehicles,
ITS(21), No. 5, May 2020, pp. 1941-1950.
IEEE DOI
2005
Inertial odometry, inertial measurement unit (IMU),
long short term memories (LSTM), deep neural network, visual-inertial odometry
BibRef
Bai, X.W.[Xi-Wei],
Wen, W.S.[Wei-Song],
Hsu, L.T.[Li-Ta],
Robust Visual-Inertial Integrated Navigation System Aided by Online
Sensor Model Adaption for Autonomous Ground Vehicles in Urban Areas,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Shamwell, E.J.[E. Jared],
Lindgren, K.[Kyle],
Leung, S.[Sarah],
Nothwang, W.D.[William D.],
Unsupervised Deep Visual-Inertial Odometry with Online Error
Correction for RGB-D Imagery,
PAMI(42), No. 10, October 2020, pp. 2478-2493.
IEEE DOI
2009
Cameras, Trajectory, Image reconstruction,
Simultaneous localization and mapping, Estimation, Visualization,
neural networks
BibRef
Niu, Z.[Zun],
Guo, F.[Fugui],
Shuai, Q.Q.[Qiang-Qiang],
Li, G.C.[Guang-Chen],
Zhu, B.C.[Bo-Cheng],
The Integration of GPS/BDS Real-Time Kinematic Positioning and
Visual-Inertial Odometry Based on Smartphones,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Cui, L.[Langfu],
Zhang, Q.Z.[Qing-Zhen],
Yang, L.M.[Li-Man],
Bai, C.G.[Cheng-Gang],
A Performance Prediction Method Based on Sliding Window Grey Neural
Network for Inertial Platform,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Morales, J.J.[Joshua J.],
Khalife, J.J.[Joe J.],
Kassas, Z.M.[Zaher M.],
Information Fusion Strategies for Collaborative Inertial Radio SLAM,
ITS(23), No. 8, August 2022, pp. 12935-12952.
IEEE DOI
2208
Global navigation satellite system,
Simultaneous localization and mapping, Radio navigation,
SLAM
BibRef
Liu, X.Y.[Xin-Yu],
Zhou, Q.F.[Qing-Feng],
Chen, X.[Xiang],
Fan, L.S.[Li-Sheng],
Cheng, C.T.[Chi-Tsun],
Bias-Error Accumulation Analysis for Inertial Navigation Methods,
SPLetters(29), 2022, pp. 299-303.
IEEE DOI
2202
Measurement uncertainty, Distortion measurement, Trajectory,
Temperature measurement, Time measurement, Inertial navigation, sensor arrays
BibRef
Jung, J.H.[Jae Hyung],
Cha, J.[Jaehyuck],
Chung, J.Y.[Jae Young],
Kim, T.I.[Tae Ihn],
Seo, M.H.[Myung Hwan],
Park, S.Y.[Sang Yeon],
Yeo, J.Y.[Jong Yun],
Park, C.G.[Chan Gook],
Monocular Visual-Inertial-Wheel Odometry Using Low-Grade IMU in Urban
Areas,
ITS(23), No. 2, February 2022, pp. 925-938.
IEEE DOI
2202
Land vehicles, Visualization, Global navigation satellite system,
Urban areas, Fuses, Accelerometers, Kalman filters, observability analysis
BibRef
Fu, D.[Dong],
Xia, H.[Hao],
Liu, Y.J.[Yu-Jie],
Qiao, Y.Y.[Yan-You],
VINS-Dimc: A Visual-Inertial Navigation System for Dynamic
Environment Integrating Multiple Constraints,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Sun, J.[Jin],
Ye, Q.Q.[Qian-Qi],
Lei, Y.[Yue],
In-Motion Alignment Method of SINS Based on Improved Kalman Filter
under Geographic Latitude Uncertainty,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link
2206
Strapdown Inertial Navigation System.
BibRef
Li, Y.[You],
Chen, R.Z.[Rui-Zhi],
Niu, X.J.[Xiao-Ji],
Zhuang, Y.[Yuan],
Gao, Z.Z.[Zhou-Zheng],
Hu, X.[Xin],
El-Sheimy, N.[Naser],
Inertial Sensing Meets Machine Learning: Opportunity or Challenge?,
ITS(23), No. 8, August 2022, pp. 9995-10011.
IEEE DOI
2208
Sensors, Inertial sensors, Calibration, Inertial navigation,
Maximum likelihood estimation, Data models, Time series analysis,
location-based service
BibRef
Gao, F.Z.[Fang-Zheng],
Tang, W.J.[Wen-Jun],
Huang, J.[Jiacai],
Chen, H.Y.[Hai-Yang],
Positioning of Quadruped Robot Based on Tightly Coupled LiDAR Vision
Inertial Odometer,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Liu, H.[Hong],
Pan, S.[Shuguo],
Gao, W.[Wang],
Ma, C.[Chun],
Jia, F.S.[Feng-Shuo],
Lu, X.Y.[Xin-Yu],
LIDAR-Inertial Real-Time State Estimator with Rod-Shaped and Planar
Feature,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Zhang, L.[Liang],
Zhang, T.[Tao],
Wei, H.Y.[Hong-Yu],
A Novel Robust Inertial and Ultra-Short Baseline Integrated
Navigation Strategy Under the Influence of Motion Effect,
ITS(23), No. 10, October 2022, pp. 19323-19334.
IEEE DOI
2210
Navigation, Acoustics, Transponders, Vehicle dynamics, Delay effects,
Heuristic algorithms, Earth, USBL, robust filter, motion effect,
integrated navigation
BibRef
Bao, J.F.[Jun-Fang],
Li, J.L.[Jian-Li],
Qu, C.Y.[Chun-Yu],
Li, Y.Z.[Yun-Zhu],
Multi-Node Motion Estimation Method Based on B-Spline of Array
Position and Orientation System,
RS(15), No. 11, 2023, pp. 2892.
DOI Link
2306
inertial measurement units.
BibRef
Zhang, H.Y.[Hao-Yue],
Xu, P.[Peng],
Ye, Z.Q.[Zong-Qi],
Ye, D.[Dong],
Qiang, L.E.[Li-E],
Luo, Z.[Ziren],
Qi, K.Q.[Ke-Qi],
Wang, S.X.[Shao-Xin],
Cai, Z.M.[Zhi-Ming],
Wang, Z.L.[Zuo-Lei],
Lei, J.G.[Jun-Gang],
Wu, Y.L.[Yue-Liang],
A Systematic Approach for Inertial Sensor Calibration of Gravity
Recovery Satellites and Its Application to Taiji-1 Mission,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link
2308
BibRef
Zhi, M.[Meixia],
Deng, C.[Chen],
Zhang, H.J.[Hong-Juan],
Tang, H.Q.[Hong-Qiong],
Wu, J.[Jiao],
Li, B.[Bijun],
RNGC-VIWO: Robust Neural Gyroscope Calibration Aided
Visual-Inertial-Wheel Odometry for Autonomous Vehicle,
RS(15), No. 17, 2023, pp. 4292.
DOI Link
2310
BibRef
Jin, Y.Q.[Yu-Qiang],
Zhang, W.A.[Wen-An],
Sun, H.[Hu],
Yu, L.[Li],
Learning-Aided Inertial Odometry With Nonlinear State Estimator on
Manifold,
ITS(24), No. 9, September 2023, pp. 9792-9803.
IEEE DOI
2310
BibRef
Wang, J.[Jinbo],
Torres, H.[Hector],
Klein, P.[Patrice],
Wineteer, A.[Alexander],
Zhang, H.[Hong],
Menemenlis, D.[Dimitris],
Ubelmann, C.[Clement],
Rodriguez, E.[Ernesto],
Increasing the Observability of Near Inertial Oscillations by a
Future ODYSEA Satellite Mission,
RS(15), No. 18, 2023, pp. 4526.
DOI Link
2310
BibRef
Wang, Z.[Zhong],
Zhang, L.[Lin],
Shen, Y.[Ying],
Zhou, Y.C.[Yi-Cong],
D-LIOM: Tightly-Coupled Direct LiDAR-Inertial Odometry and Mapping,
MultMed(25), 2023, pp. 3905-3920.
IEEE DOI
2310
BibRef
Demkowicz, J.[Jerzy],
Measuring Tilt with an IMU Using the Taylor Algorithm,
RS(16), No. 15, 2024, pp. 2800.
DOI Link
2408
BibRef
Yi, J.H.[Jin-Hui],
Ma, Y.[Yuebo],
Long, H.[Hongfeng],
Zhu, Z.J.[Zi-Jian],
Zhao, R.[Rujin],
Tightly Coupled Visual-Inertial Fusion for Attitude Estimation of
Spacecraft,
RS(16), No. 16, 2024, pp. 3063.
DOI Link
2408
BibRef
Luo, J.X.[Jin-Xin],
Wu, K.[Kunyang],
Wang, Y.T.[Yi-Tian],
Wang, T.H.[Tian-Hao],
Zhang, G.[Guanyu],
Liu, Y.[Yang],
An Improved UKF for IMU State Estimation Based on Modulation LSTM
Neural Network,
ITS(25), No. 9, September 2024, pp. 10702-10711.
IEEE DOI
2409
Long short term memory, Modulation, Neural networks,
Kalman filters, Deep learning, Data models, State estimation, IMU, UKF,
equal spacing sigma sampling
BibRef
Or, B.[Barak],
Segol, N.[Nimrod],
Eweida, A.[Areej],
Freydin, M.[Maxim],
Learning Position From Vehicle Vibration Using an Inertial
Measurement Unit,
ITS(25), No. 9, September 2024, pp. 10766-10776.
IEEE DOI
2409
Roads, Sensors, Position measurement,
Global navigation satellite system, Automobiles, supervised learning
BibRef
Chen, C.[Changhao],
Pan, X.[Xianfei],
Deep Learning for Inertial Positioning: A Survey,
ITS(25), No. 9, September 2024, pp. 10506-10523.
IEEE DOI
2409
Robot sensing systems, Inertial navigation, Deep learning,
Pedestrians, Surveys, Inertial sensors, Noise, Inertial navigation,
visual-inertial odometry
BibRef
Herath, S.[Sachini],
Caruso, D.[David],
Liu, C.[Chen],
Chen, Y.F.[Yu-Fan],
Furukawa, Y.[Yasutaka],
Neural Inertial Localization,
CVPR22(6594-6603)
IEEE DOI
2210
Location awareness, Inertial sensors, Soft sensors,
Inertial navigation, Transformers, Energy efficiency, Motion and tracking
BibRef
Örnhag, M.V.[Marcus Valtonen],
Persson, P.[Patrik],
Wadenbäck, M.[Mårten],
Åström, K.[Kalle],
Heyden, A.[Anders],
Trust Your IMU: Consequences of Ignoring the IMU Drift,
WAD22(4467-4476)
IEEE DOI
2210
Measurement units, Codes, Inertial navigation,
Distortion, Real-time systems
BibRef
Rebello, J.[Jason],
Li, C.[Chunshang],
Waslander, S.L.[Steven L.],
DC-VINS: Dynamic Camera Visual Inertial Navigation System with Online
Calibration,
TradiCV21(2559-2568)
IEEE DOI
2112
Visualization, Simultaneous localization and mapping, Dynamics,
Pipelines, Cameras, Calibration, Trajectory
BibRef
Petit, B.,
Guillemard, R.,
Gay-Bellile, V.,
Time Shifted IMU Preintegration for Temporal Calibration in
Incremental Visual-Inertial Initialization,
3DV20(171-179)
IEEE DOI
2102
Time measurement, Visualization, Optimization, Location awareness,
Real-time systems, Gyroscopes, Calibration, SLAM, IMU, Initialization,
Camera
BibRef
Li, C.,
Waslander, S.L.,
Towards End-to-end Learning of Visual Inertial Odometry with an EKF,
CRV20(190-197)
IEEE DOI
2006
visual inertial odometry, localization, deep learning,
robo-centric EKF, supervised deep learning
BibRef
Nisar, B.[Barza],
Foehn, P.[Philipp],
Falanga, D.[Davide],
Scaramuzza, D.[Davide],
VIMO:
Simultaneous Visual Inertial Model-based Odometry and Force Estimation,
RSS19. (xx-yy).
HTML Version.
2009
Code, Odometry. Extends the capability of a typical optimization-based Visual-Inertial
Odometry framework to jointly estimate external forces in addition to
the robot state and IMU bias
BibRef
Liu, H.,
Chen, M.,
Zhang, G.,
Bao, H.,
Bao, Y.,
ICE-BA: Incremental, Consistent and Efficient Bundle Adjustment for
Visual-Inertial SLAM,
CVPR18(1974-1982)
IEEE DOI
1812
Simultaneous localization and mapping, Visualization,
Optimization, Task analysis,Time measurement, Cameras
BibRef
Ovrén, H.,
Forssén, P.,
Spline Error Weighting for Robust Visual-Inertial Fusion,
CVPR18(321-329)
IEEE DOI
1812
Splines (mathematics), Cameras, Videos, Approximation error,
Trajectory, Discrete Fourier transforms, Standards
BibRef
Khattak, S.[Shehryar],
Papachristos, C.[Christos],
Alexis, K.[Kostas],
Marker Based Thermal-Inertial Localization for Aerial Robots in
Obscurant Filled Environments,
ISVC18(565-575).
Springer DOI
1811
BibRef
Khattak, S.[Shehryar],
Papachristos, C.[Christos],
Alexis, K.[Kostas],
Vision-Depth Landmarks and Inertial Fusion for Navigation in Degraded
Visual Environments,
ISVC18(529-540).
Springer DOI
1811
BibRef
Yan, H.[Hang],
Shan, Q.[Qi],
Furukawa, Y.[Yasutaka],
RIDI: Robust IMU Double Integration,
ECCV18(XIII: 641-656).
Springer DOI
1810
BibRef
Solin, A.,
Cortes, S.,
Rahtu, E.,
Kannala, J.,
PIVO: Probabilistic Inertial-Visual Odometry for Occlusion-Robust
Navigation,
WACV18(616-625)
IEEE DOI
1806
distance measurement, image sensors, image sequences,
inertial navigation, inference mechanisms, probability,
Visualization
BibRef
Fei, X.H.[Xiao-Han],
Soatto, S.[Stefano],
Visual-Inertial Object Detection and Mapping,
ECCV18(XI: 318-334).
Springer DOI
1810
BibRef
Dong, J.M.[Jing-Ming],
Fei, X.H.[Xiao-Han],
Soatto, S.[Stefano],
Visual-Inertial-Semantic Scene Representation for 3D Object Detection,
CVPR17(3567-3577)
IEEE DOI
1711
Detectors, Real-time systems, Semantics,
Sensor phenomena and characterization,
Visualization
BibRef
Li, Z.Q.[Zi-Qiang],
Liu, X.H.[Xiao-Hui],
Liu, Y.X.[Ying-Xiang],
Li, B.[Boyu],
An inertial information assisted acquisition algorithm of modernized
navigation signal,
ICIVC17(836-841)
IEEE DOI
1708
Accelerometers, Navigation, Signal to noise ratio, GNSS, INS,
acquisition, high dynamic, modernized, weak, signal
BibRef
Ahmed, H.,
Tahir, M.,
Accurate Attitude Estimation of a Moving Land Vehicle Using Low-Cost
MEMS IMU Sensors,
ITS(18), No. 7, July 2017, pp. 1723-1739.
IEEE DOI
1706
Acceleration, Accelerometers, Estimation, Gyroscopes,
Micromechanical devices, Sensors, Vehicles, Kalman filter, MEMS IMU,
Vehicle attitude, attitude estimation, external, acceleration
BibRef
Kawasaki, H.[Hideaki],
Anzai, S.[Shojiro],
Koizumi, T.[Toshio],
Study On Improvement Of Accuracy In Inertial Photogrammetry By
Combining Images With Inertial Measurement Unit,
ISPRS16(B5: 501-505).
DOI Link
1610
BibRef
Molina, P.,
Angelats, E.,
Colomina, I.,
Latorre, A.,
Montaño, J.,
Wis, M.,
The Perigeo Project: Inertial and Imaging Sensors Processing,
Integration and Validation on UAV Platforms for Space Navigation,
EuroCOW14(79-85).
DOI Link
1404
BibRef
di Corato, F.,
Innocenti, M.,
Pollini, L.,
Visual-inertial navigation with guaranteed convergence,
WORV13(152-157)
IEEE DOI
1307
Kalman filters
BibRef
Cheuk, C.M.[Chi Ming],
Lau, T.K.[Tak Kit],
Lin, K.W.[Kai Wun],
Liu, Y.[Yunhui],
Automatic calibration for inertial measurement unit,
ICARCV12(1341-1346).
IEEE DOI
1304
BibRef
Hun, L.C.[Lim Chot],
Sze, L.T.[Lim Tien],
Chet, K.V.[Koo Voon],
A PC-based orientation sensing using 9-DOF strapdown inertial
measurement unit,
ICARCV12(229-234).
IEEE DOI
1304
BibRef
Shen, Z.[Zhi],
Georgy, J.[Jacques],
Noureldin, A.[Aboelmagd],
Enabling accurate low cost positioning in denied GPS environments with
nonlinear error models of inertial systems,
CGC10(43).
PDF File.
1006
BibRef
Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Vehicle Trajectory Planning .