Interacting Multiple Model Adaptive Unscented Kalman Filter for Accurate Localization of a High-Dynamic Motion Mobile Robot Using Wireless Sensor Network
(*) Corresponding author
Accurate and precise positioning of a mobile robot is a critical problem in the navigation system, and it has become difficult for localization indoors and in GPS-denied areas. Odometry, which is based on dead reckoning, cannot usually provide long-term accurate position estimates. As a result, integrating encoder-based odometry with Wireless Sensor Network (WSN) measurements is recommended as a good solution for minimizing divergences due to uncertainties. The Kalman filtering technique is used to improve state estimation and measurement fusion. Therefore, this paper describes the design and implementation of an Unscented Kalman Filter (UKF) with an adaptive tuning technique to adjust the process noise covariance matrix, resulting in better position estimation, particularly in high-dynamic motions of the mobile robot. Furthermore, for a mobile robot, this work proposes an Interacting Multiple Model (IMM) method with two dynamic motion models, i.e. Constant Velocity (CV) and Coordinated Turn (CT), to deliver high performance with minimal computational overhead. Several experiments on two types of mobile robots were conducted to evaluate and compare the effectiveness of the proposed localization algorithm. The proposed localization technique outperformed the other three methods and demonstrated its effectiveness in high dynamic motions due to the adaptive tuning system.
Copyright © 2022 Praise Worthy Prize - All rights reserved.
M. Hayajneh, Experimental validation of integrated and robust control system for mobile robots, International Journal of Dynamics and Control , vol. 9, no. 4, pp. 1491-1504, 2021.
S. Mutawe, M. Hayajneh and S. BaniHani, Robust Path Following Controllers for Quadrotor and Ground Robot, in International Conference on Electrical, Communication, and Computer Engineering (ICECCE), 2021.
S. Mutawe, M. Hayajneh, S. BaniHani and M. Al Qaderi, Simulation of Trajectory Tracking and Motion Coordination for Heterogeneous Multi-Robots System, Jordan Journal of Mechanical & Industrial Engineering, vol. 15, no. 4, pp. 337-345, 2021.
H. Obeidat, W. Shuaieb, O. Obeidat and R. Abd-Alhameed, A review of indoor localization techniques and wireless technologies, Wireless Personal Communications, vol. 119, no. 1, pp. 289-327, 2021.
W. Chen and T. Zhang, An indoor mobile robot navigation technique using odometry and electronic compass, International Journal of Advanced Robotic Systems, vol. 14, no. 3, pp. 1-15, 2017.
S. BaniHani, M. Hayajneh, A. Al-Jarrah and S. Mutawe, New control approaches for trajectory tracking and motion planning of unmanned tracked robot, Advances in Electrical and Electronic Engineering, vol. 19, no. 1, pp. 42-56, 2021.
Mutawe, S., Hayajneh, M., Al Momani, F., Accurate State Estimations and Velocity Drifting Compensations Using Complementary Filters for a Quadrotor in GPS-Drop Regions, (2021) International Journal on Engineering Applications (IREA), 9 (6), pp. 317-326.
A. P. Moreira, P. Costa and J. Lima, New approach for beacons based mobile robot localization using Kalman filters, Procedia Manufacturing, vol. 51, pp. 512-519, 2020.
Ali Salman, S., Khasawneh, Q., Jaradat, M., Alramlawi, M., Indoor Navigation System of Omni-Directional Mobile Robot Based on Static Obstacles Avoidance, (2020) International Review of Automatic Control (IREACO), 13 (1), pp. 27-37.
Z. Li, Z. Su and T. Yang, Design of Intelligent Mobile Robot Positioning Algorithm Based on IMU/Odometer/Lidar, in International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC), 2019.
D. R. -Y. Phang, W. -K. Lee, N. Matsuhira and P. Michail, Enhanced Mobile Robot Localization with Lidar and IMU Sensor, in IEEE International Meeting for Future of Electron Devices, Kansai , 2019.
Alyaoui, N., Zaatouri, I., Saidi, W., Cherif, S., Kachouri, A., Study of the Impact of Various Objective Functions on the Heterogeneous Wireless Sensor Networks, (2022) International Journal on Engineering Applications (IREA), 10 (1), pp. 66-76.
Bani Yassein, M., Altiti, O., Performance Evaluation of the Objective Functions for Digital Media in Internet of Things (IoT), (2020) International Journal on Communications Antenna and Propagation (IRECAP), 10 (5), pp. 345-352.
Y. Xu, Y. S. Shmaliy, X. Chen, Y. Li and W. Ma, Robust inertial navigation system/ultra wide band integrated indoor quadrotor localization employing adaptive interacting multiple model-unbiased finite impulse response/Kalman filter estimator, Aerospace Science and Technology, vol. 98, p. 105683, 2020.
H. Wu, X. Wu and G. Tian, Indoor robot localization based on single RFID tag, Artificial Life and Robotics, vol. 23, no. 3, pp. 373-379, 2018.
B. Tao, H. Wu, Z. Gong, Z. Yin and H. Ding, An RFID-Based Mobile Robot Localization Method Combining Phase Difference and Readability, IEEE Transactions on Automation Science and Engineering, vol. 18, no. 3, pp. 1406-1416, 2021.
L. Zhang, Z. Chen, W. Cui, B. Li, C. Chen, Z. Cao and K. Gao, WiFi-Based Indoor Robot Positioning Using Deep Fuzzy Forests, IEEE Internet of Things Journal, vol. 7, no. 11, pp. 10773-10781, 2020.
A. P. Neto and F. Tonidandel, Analysis of WiFi localization techniques for kidnapped robot problem, in IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), 2022.
G. Fu, J. Zhang, W. Chen, F. Peng, P. Yang and C. Chen, Precise Localization of Mobile Robots via Odometry and Wireless Sensor Network, Journal of Advanced Robotic Systems, vol. 10, no. 4, pp. 1-13, 2013.
M. Sun, Y. Gao, Z. Jiao, Y. Xu, Y. Zhuang and P. Qian, RTS assisted Kalman filtering for robot localization using UWB measurement, Mobile Networks and Applications, pp. 1-10, 2022.
V. Magnago, P. Corbalán, G. P. Picco, L. Palopoli and D. Fontanelli, Robot localization via odometry-assisted ultra-wideband ranging with stochastic guarantees, in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.
A. Eman and H. Ramdane, Mobile Robot Localization Using Extended Kalman Filter, in 3rd International Conference on Computer Applications & Information Security (ICCAIS), 2020.
L. Chen, H. Hu and K. McDonald-Maier, EKF Based Mobile Robot Localization, in Third International Conference on Emerging Security Technologies, 2012.
G. Zhou, J. Luo, S. Xu, S. Zhang, S. Meng and K. Xiang, An EKF-based multiple data fusion for mobile robot indoor localization, Assembly Automation, vol. 41, no. 3, pp. 274-282, 2021.
J. Simanek, M. Reinstein and V. Kubelka, Evaluation of the EKF-Based Estimation Architectures for Data Fusion in Mobile Robots, EEE/ASME Transactions on Mechatronics, vol. 20, no. 2, pp. 985-990, 2015.
Y. E. Kim, H. H. Kang and C. K. Ahn, Two-layer nonlinear FIR filter and unscented Kalman filter fusion with application to mobile robot localization., IEEE Access, pp. 87173-87183, 2020.
L. Lasmadi, F. Kurniawan, D. Dermawan and G. Pratama, Mobile robot localization via unscented kalman filter., in 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2019.
D. Luigi, W. Lucia, P. Muraca and P. Pugliese, Mobile robot localization via EKF and UKF: A comparison based on real data, Robotics and Autonomous Systems, vol. 74, pp. 122-127, 2015.
I. Ullah, Y. Shen, X. Su, C. Esposito and C. Choi, A Localization Based on Unscented Kalman Filter and Particle Filter Localization Algorithms, IEEE Access, vol. 8, pp. 2233-2246, 2020.
L. Lasmadi, F. Kurniawan, D. Dermawan and G. N. P. Pratama, Mobile Robot Localization via Unscented Kalman Filter, in 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2019.
B. Zheng, P. Fu, B. Li and X. Yuan, A robust adaptive unscented Kalman filter for nonlinear estimation with uncertain noise covariance, Sensors, vol. 18, no. 3, pp. 1-15, 2018.
S. Qi and H. Jian-Da., An adaptive UKF algorithm for the state and parameter estimations of a mobile robot, Acta Automatica Sinica, vol. 34, no. 1, pp. 72-79, 2008.
M. A. Gomaa, O. De Silva, G. K. Mann and R. G. Gosine, Interacting Multiple Model Navigation System for Quadrotor Micro Aerial Vehicles Subject to Rotor Drag, in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
L. Zhu and X. Cheng, High manoeuvre target tracking in coordinated turns, IET Radar, Sonar & Navigation, vol. 9, no. 8, pp. 1078-1087, 2015.
X. R. Li and V. P. Jilkov, Survey of maneuvering target tracking. Part I: dynamic models, IEEE Transactions on aerospace and electronic systems , vol. 39, no. 4, pp. 1333-1364, 2003.
E. A. Wan and R. Van Der Merwe, The unscented Kalman filter for nonlinear estimation, in the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, 2000.
F. Jiancheng and Y. Sheng, Study on innovation adaptive EKF for in-flight alignment of airborne POS, IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 4, pp. 1378-1388, 2011.
- There are currently no refbacks.
Please send any question about this web site to firstname.lastname@example.org
Copyright © 2005-2023 Praise Worthy Prize