[1] Siegwart, R., Nourbakhsh, I.R., and Scaramuzza, D.: ‘Introduction to autonomous mobile robots’ MIT press, 2011.
[2] Zheng, L., Zhan, X., Zhang, X., Wang, S., and Yuan, W.: ‘Heading estimation for multimode pedestrian dead reckoning’, IEEE Sensors Journal, vol.20, no.15, pp. 8731-8739, 2020.
[3] Madray, I., Suire, J., Desforges, J., and Madani, M.R. ‘Relative angle correction for distance estimation using K-nearest neighbors’, EEE Sensors Journal, vol. 20, no. 14, pp. 8155–8163, Jul. 2020
[4] Guo, S., Zhang, Y., Gui, X., and Han, L.: ‘An improved PDR/UWB integrated system for indoor navigation applications’, IEEE Sensors Journal, vol. 20, no. 14, pp. 8046–8061, Jul. 2020.
[5] Rauniyar, S., Bhalla, S., Choi, D., and Kim, D.: ‘EKF-SLAM for Quadcopter Using Differential Flatness-Based LQR Control’, Electronics, vol. 12, no. 5, p. 1113, 2023.
[6] Leonard, J.J., and Durrant-Whyte, H.F.: ‘Directed sonar sensing for mobile robot navigation’, Springer Science & Business Media, 2012.
[7] Chen, L., Hu, H., and McDonald-Maier, K.: ‘Ekf based mobile robot localization’, in Proc. IEEE Int. Conf. on Industrial Technology (ICIT), Athens, Greece, 2012, pp. 149–154.
[8] Suliman, C., Cruceru, C., and Moldoveanu, F.: ‘Mobile robot position estimation using the Kalman filter’, Acta Marisiensis, Seria Technologica, vol. 6, pp. 75–80, 2009.
[9] Zhang, H., Chen, N., and Fan, G.: ‘An Improved Localization Algorithm for Intelligent Robot’, in Proc. IEEE Int. Conf. on Artificial Intelligence and Big Data (ICAIBD), Chengdu, China, 2019, pp. 1–5.
[10] Lin, H.-Y. and M.-C. Yeh, ‘Drift-Free Visual SLAM for Mobile Robot Localization by Integrating UWB Technology’. IEEE Access, vol. 10, pp. 93636–93645, 2022.
[11] Coelho, F.O., et al. ‘Ekf and computer vision for mobile robot localization’, in Proc. 13th APCA Int. Conf. Automatic Control and Soft Computing (CONTROLO), 2018.
[12] Zhang, F., et al. ‘A novel strategy of localization based on EKF for mobile robot’, in Proceedings of the 33rd Chinese Control Conference. 2014.
[13] Chen, L., H. Hu, and K. McDonald-Maier. ‘Ekf based mobile robot localization’, n Proc. 3rd Int. Conf. Emerging Security Technologies, 2012.
[14] Joon, A. and W. Kowalczyk. ‘Leader Following Control of Non-holonomic Mobile Robots Using EKF-based Localization’ in 2023 27th International Conference on Methods and Models in Automation and Robotics (MMAR). 2023.
[15] Sun, Z., et al., ‘Multi-Risk-RRT: An Efficient Motion Planning Algorithm for Robotic Autonomous Luggage Trolley Collection at Airports’ , IEEE Transactions on Intelligent Vehicles, vol. 9, pp. 3450-3463, 2024.
[16] Mizuno, M. and T. Kubota. ‘A new path planning architecture to consider motion uncertainty in natural environment’, in 2020 IEEE International Conference on Robotics and Automation (ICRA). 2020. IEEE.
[17] Cao, M., Zhou, X., and Ju, Y., ‘Robot Motion Planning Based on Improved RRT Algorithm and RBF Neural Network Sliding’, IEEE Access, vol. 11, pp.121295-121305, 2023.
[18] Yu, Z., Jiang, X., and Liu, Y., ‘Pose estimation of an aerial construction robot based on motion and dynamic constraints’, Robotics and Autonomous Systems, vol. 172, p. 104591, 2024.
[19] Brigadnov, I., Lutonin, A., and Bogdanova, K., ‘Error State Extended Kalman Filter Localization for Underground Mining Environments’, Symmetry, vol. 15, no. 2, p. 344, 2023.
[20] Panigrahi, P.K., and Bisoy, S.K.: ‘Localization strategies for autonomous mobile robots: A review’, Journal of King Saud University-Computer and Information Sciences, vol. 34, no. 8, pp. 6019-6039, 2022.
[21] Kong, F., Chen, Y., Xie, J., Zhang, G., and Zhou, Z.: ‘Mobile robot localization based on extended kalman filter’, in Proceedings of IEEE Conference, 2006, pp. 9242–9246 .
[22] Karaman, S. and E. Frazzoli. 'Optimal kinodynamic motion planning using incremental sampling-based methods', in 49th IEEE conference on decision and control (CDC). 2010.
[23] Karaman, S. and Frazzoli, E. 'Sampling-based algorithms for optimal motion planning', The International Journal of Robotics Research, vol. 30, no. 7, pp. 846–894, 2011.
[24] Noreen, I., Khan, A., and Habib, Z., 'Optimal path planning using RRT* based approaches: a survey and future directions', International Journal of Advanced Computer Science and Applications, vol. 7, no. 11, 2016.
[25] Szabat, K., et al., 'A fuzzy unscented Kalman filter in the adaptive control system of a drive system with a flexible joint', Energies, vol. 13, no. 8, p. 2056, 2020.
[26] Woo, R., E.-J. Yang, and D.-W. Seo, 'A fuzzy-innovation-based adaptive Kalman filter for enhanced vehicle positioning in dense urban environments', Sensors, vol. 19, no. 5, p. 1142, 2019
[27] C.-Y. Yang, H. Samani, Z. Tang, and C. Li, 'Implementation of extended Kalman filter for localization of ambulance robot', International Journal of Intelligent Robotics and Applications, vol. 8, no. 4, pp. 960–973, Jun. 2024.
[28] Y. Wang, Q. Zhang, and J. Liu,'Application of a Modified IEKF Algorithm in Mobile Robot Localization', in Proc. 2022 4th Int. Conf. on Robotics, Intelligent Control and Artificial Intelligence (RICAI), Guangzhou, China, Dec. 2022, pp. 53–57.