ROS-based multi-sensor integrated localization system for cost-effective and accurate indoor navigation system
Author:
Funder
Institut Teknologi Bandung
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41315-024-00350-1.pdf
Reference42 articles.
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2. Aqel, M.O., Marhaban, M.H., Saripan, M.I., Ismail, N.B.: Review of visual odometry: types, approaches, challenges, and applications. Springerplus 5, 1–26 (2016)
3. Bhargava, M., Mehta, R., Adhikari, C.D., Sivanathan, K.: Towards development of performance metrics for benchmarking slam algorithms. J. Phys. Conf. Ser. 1964(6), 062115 (2021)
4. Brossard M., Bonnabel, S.: Learning wheel odometry and IMU errors for localization. In: 2019 International Conference on Robotics and Automation (ICRA), pp. 291–297 (2019). https://doi.org/10.1109/ICRA.2019.8794237
5. Chang, L., Niu, X., Liu, T.: GNSS/IMU/ODO/lidar-SLAM integrated navigation system using IMU/ODO pre-integration. Sensors 20(17), 4702 (2020). https://doi.org/10.3390/s20174702
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