Fetching the paper…
Reading the bibliography…
Positioning is a prominent field of study, notably focusing on Visual Inertial Odometry (VIO) and Simultaneous Localization and Mapping (SLAM) methods.
Bottou, L. et al., 1991. Stochastic gradient learning in neural networks. Proceedings of Neuro-Nımes
1991
Earlier work this paper cites.
Horn, J., Schmidt, G., 1995. Continuous localization of a mobile robot based on 3D-laser-range-data, predicted sensor images, and dead-reckoning. Robotics and Autonomous Systems
1995
Earlier work this paper cites.
Srinivasan, M. V., Chahl, J. S., Zhang, S.-W., 1997. Robot navigation by visual dead-reckoning: inspiration from insects. International Journal of Pattern Recognition and Artificial Intelligence
1997
Earlier work this paper cites.
Sussman, M., Fatemi, E., 1999. An efficient, interface-preserving level set redistancing algorithm and its application to interfacial incompressible fluid flow. SIAM Journal on scientific computing
1999
Earlier work this paper cites.
Øvstedal, O., 2002. Absolute positioning with single-frequency GPS receivers. GPS Solutions
2002
Earlier work this paper cites.
Rivard, F., Bisson, J., Michaud, F., Létourneau, D., 2008. Ultrasonic relative positioning for multi-robot systems. 2008 IEEE International Conference on Robotics and Automation , IEEE, 323–328
2008
Earlier work this paper cites.
Schleicher, D., Bergasa, L. M., Ocaña, M., Barea, R., López, M. E., 2009. Real-time hierarchical outdoor SLAM based on stereovision and GPS fusion. IEEE Transactions on Intelligent Transportation Systems
2009
Earlier work this paper cites.
Williams, B., Cummins, M., Neira, J., Newman, P., Reid, I., Tardós, J., 2009. A comparison of loop closing techniques in monocular SLAM. Robotics and Autonomous Systems
2009
Earlier work this paper cites.
Weiss, S., Scaramuzza, D., Siegwart, R., 2011. Monocular-SLAM–based navigation for autonomous micro helicopters in GPS-denied environments. Journal of Field Robotics
2011
Earlier work this paper cites.
Botterill, T., Mills, S., Green, R., 2012. Correcting scale drift by object recognition in single-camera SLAM. IEEE transactions on cybernetics
2012
Earlier work this paper cites.
Kerl, C., Sturm, J., Cremers, D., 2013. Dense visual slam for rgb-d cameras. 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems , IEEE, 2100–2106
2013
Earlier work this paper cites.
Forster, C., Pizzoli, M., Scaramuzza, D., 2014. Svo: Fast semi-direct monocular visual odometry. 2014 IEEE international conference on robotics and automation (ICRA) , IEEE, 15–22
2014
Cited alongside, same era.
Bresson, G., Aufrère, R., Chapuis, R., 2015. Improving slam with drift integration. 2015 IEEE 18th International Conference on Intelligent Transportation Systems , IEEE, 2700–2706
2015
Cited alongside, same era.
Mur-Artal, R., Montiel, J. M. M., Tardos, J. D., 2015. ORB-SLAM: a versatile and accurate monocular SLAM system. IEEE transactions on robotics
2015
Cited alongside, same era.
Hening, S., Ippolito, C. A., Krishnakumar, K. S., Stepanyan, V., Teodorescu, M., 2017. 3d lidar slam integration with gps/ins for uavs in urban gps-degraded environments. AIAA Information Systems-AIAA Infotech@ Aerospace , 0448
2017
Cited alongside, same era.
Qin, T., Li, P., Shen, S., 2018. Vins-mono: A robust and versatile monocular visual-inertial state estimator. IEEE Transactions on Robotics
2018
Later among the works it cites.
Huai, J., Zhang, Y., Yilmaz, A., 2019. The mobile ar sensor logger for android and ios devices. 2019 IEEE SENSORS , IEEE, 1–4
2019
Later among the works it cites.
Kiss-Illés, D., Barrado, C., Salamí, E., 2019. GPS-SLAM: An augmentation of the ORB-SLAM algorithm. Sensors
2019
Later among the works it cites.
Bai, N., Tian, Y., Liu, Y., Yuan, Z., Xiao, Z., Zhou, J., 2020. A high-precision and low-cost IMU-based indoor pedestrian positioning technique. IEEE Sensors Journal
2020
Later among the works it cites.
Li, Y., Brasch, N., Wang, Y., Navab, N., Tombari, F., 2020. Structure-slam: Low-drift monocular slam in indoor environments. IEEE Robotics and Automation Letters
2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Nobre, F., Kasper, M., Heckman, C., 2017. Drift-correcting self-calibration for visual-inertial slam. 2017 IEEE International Conference on Robotics and Automation (ICRA) , IEEE, 6525–6532
2017
Cited alongside, same era.
OpenStreetMap contributors, 2017. Planet dump retrieved from https://planet.osm.org . https://www.openstreetmap.org
2017
Cited alongside, same era.
Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., Lerer, A., 2017. Automatic differentiation in PyTorch
2017
Cited alongside, same era.
Alsayed, Z., Bresson, G., Verroust-Blondet, A., Nashashibi, F., 2018. 2d slam correction prediction in large scale urban environments. 2018 IEEE International Conference on Robotics and Automation (ICRA) , IEEE, 5167–5174
2018
Cited alongside, same era.
Behley, J., Stachniss, C., 2018. Efficient surfel-based slam using 3d laser range data in urban environments. Robotics: Science and Systems , 2018, 59
2018
Cited alongside, same era.
Chen, C., Zhu, H., 2018. Visual-inertial SLAM method based on optical flow in a GPS-denied environment. Industrial Robot: An International Journal
2018
Cited alongside, same era.
Later among the works it cites.
Liu, J., Meng, Z., 2020. Visual slam with drift-free rotation estimation in manhattan world. IEEE Robotics and Automation Letters
2020
Later among the works it cites.
Zhao, Y., Smith, J. S., Karumanchi, S. H., Vela, P. A., 2020. Closed-loop benchmarking of stereo visual-inertial slam systems: Understanding the impact of drift and latency on tracking accuracy. 2020 IEEE International Conference on Robotics and Automation (ICRA) , IEEE, 1105–1112
2020
Later among the works it cites.
Zhou, L., Koppel, D., Kaess, M., 2021. LiDAR SLAM with plane adjustment for indoor environment. IEEE Robotics and Automation Letters
2021
Later among the works it cites.
Li, X., Wang, W., Chen, J., Zhang, X., 2022. DR-SLAM: drift rejection SLAM with Manhattan regularity for indoor environments. Advanced Robotics
2022
Later among the works it cites.
Keitaanniemi, A., Rönnholm, P., Kukko, A., Vaaja, M. T., 2023. Drift analysis and sectional post-processing of indoor simultaneous localization and mapping (SLAM)-based laser scanning data. Automation in Construction
2023
Later among the works it cites.