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In this paper, we propose a tightly-coupled, multi-modal simultaneous localization and mapping (SLAM) framework, integrating an extensive set of sensors: IMU, cameras, multiple lidars, and Ultra-wideband (UWB) range measurements, hence referred to as VIRAL (visual-inertial-ranging-lidar) SLAM.
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2020
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H. Xu, L. Wang, Y. Zhang, K. Qiu, and S. Shen, “Decentralized visual-inertial-uwb fusion for relative state estimation of aerial swarm,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 8776–8782
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T. Shan, B. Englot, C. Ratti, and R. Daniela, “Lvi-sam: Tightly-coupled lidar-visual-inertial odometry via smoothing and mapping,” in IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2021, pp. to–be–added
2021
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2021
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H. Ye, Y. Chen, and M. Liu, “Tightly coupled 3d lidar inertial odometry and mapping,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 3144–3150
2019
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T.-M. Nguyen, M. Cao, S. Yuan, Y. Lyu, T. H. Nguyen, and L. Xie, “Liro: Tightly coupled lidar-inertia-ranging odometry,” 2021 IEEE International Conference on Robotics and Automation (ICRA), Accepted , 2020
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T. H. Nguyen, T.-M. Nguyen, and L. Xie, “Tightly-coupled ultra-wideband-aided monocular visual slam with degenerate anchor configurations,” Autonomous Robots , vol. 44, no. 8, pp. 1519–1534, 2020
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X. Zuo, Y. Yang, P. Geneva, L. Jiajun, Y. Liu, G. Huang, and M. Pollefey, “Lic-fusion 2.0: Lidar-inertial-camera odometry with sliding-window plane-feature tracking,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020, pp. 5112–5119
2020
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T. Shan, B. Englot, D. Meyers, W. Wang, C. Ratti, and R. Daniela, “Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2020, pp. 5135–5142
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T.-M. Nguyen, S. Yuan, M. Cao, Y. Lyu, T. H. Nguyen, and L. Xie, “Ntu viral: A visual-inertial-ranging-lidar dataset, from an aerial vehicle viewpoint,” The International Journal of Robotics Research. [Online]. Available: https://ntu-aris.github.io/ntu_viral_dataset/
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——, “Range-focused fusion of camera-imu-uwb for accurate and drift-reduced localization,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 1678 – 1685, 2021
2021
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D. Wisth, M. Camurri, S. Das, and M. Fallon, “Unified multi-modal landmark tracking for tightly coupled lidar-visual-inertial odometry,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 1004–1011, 2021
2021
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P. Chen, W. Shi, S. Bao, M. Wang, W. Fan, and H. Xiang, “Low-drift odometry, mapping and ground segmentation using a backpack lidar system,” IEEE Robotics and Automation Letters , 2021
2021
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T.-M. Nguyen, S. Yuan, M. Cao, Y. Lyu, T. H. Nguyen, and L. Xie, “Miliom: Tightly coupled multi-input lidar-inertia odometry and mapping,” IEEE Robotics and Automation Letters , vol. 6, no. 3, pp. 5573–5580, May 2021
2021
Closest in time.