[
1. Almeida T., Santos V., Mozos O. M., Lourenço B. (2021), Comparative Analysis of Deep Neural Networks for the Detection and Decoding of Data Matrix Landmarks in Cluttered Indoor Environments. Journal of Intelligent & Robotic Systems, 103(1), 1-14.10.1007/s10846-021-01442-x
]Search in Google Scholar
[
2. Ben Jabeur C., Seddik H. (2020), Design of a PID optimized neural networks and PD fuzzy logic controllers for a two-wheeled mobile robot, Asian Journal of Control, 22(1), 1–19.10.1002/asjc.2356
]Search in Google Scholar
[
3. Elmi Z., Efe M. Ö. (2020), Online path planning of mobile robot using grasshopper algorithm in a dynamic and unknown environment, Journal of Experimental & Theoretical Artificial Intelligence, 32, 1–19.10.1080/0952813X.2020.1764631
]Search in Google Scholar
[
4. Hadi N. H., Younus K. K. (2020), Path tracking and backstepping control for a wheeled mobile robot (WMR) in a slipping environment, IOP Conference Series: Materials Science and Engineering, 671, 1–17.10.1088/1757-899X/671/1/012005
]Search in Google Scholar
[
5. Khan H., Khatoon S., Gaur P. (2021), Comparison of various controller design for the speed control of DC motors used in two wheeled mobile robots. International Journal of Information Technology, 13(2), 713-720.10.1007/s41870-020-00577-8
]Search in Google Scholar
[
6. Long Y., Zuo Z., Su Y., Li J., Zhang H. (2020), An A*-based Bacterial Foraging Optimisation Algorithm for Global Path Planning of Unmanned Surface Vehicles, The Journal of Navigation, 73(3), 1–16.10.1017/S0373463320000247
]Search in Google Scholar
[
7. Narasimhan G. E., Bettyjane J. (2020), Implementation and study of a novel approach to control adaptive cooperative robot using fuzzy rules. International Jopurnal of Information Technology, 1–8. https://doi.org/10.1007/s41870-020-00459-z10.1007/s41870-020-00459-z
]Search in Google Scholar
[
8. Nedjah N., Junior L. S. (2019), Review of methodologies and tasks in swarm robotics towards standardization, Swarm and Evolutionary Computation, 50, 1–26.10.1016/j.swevo.2019.100565
]Search in Google Scholar
[
9. Osaba E., Del Ser J., Iglesias A., Yang X. S. (2019), Soft Computing for Swarm Robotics: New Trends and Applications, Journal of Computational Science, 39, 1–4.10.1016/j.jocs.2019.101049
]Search in Google Scholar
[
10. Pandey A., Kashyap A. K., Parhi D. R., Patle, B. K. (2019), Autonomous mobile robot navigation between static and dynamic obstacles using multiple ANFIS architecture, World Journal of Engineering, 16(2), 275–286.10.1108/WJE-03-2018-0092
]Search in Google Scholar
[
11. Pandey A., Parhi D. R. (2016), New algorithm for behaviour-based mobile robot navigation in cluttered environment using neural network architecture, World Journal of Engineering, 13(2), 129–141.10.1108/WJE-04-2016-018
]Search in Google Scholar
[
12. Pandey K. K., Parhi D. R. (2019), Trajectory Planning and the Target Search by the Mobile Robot in an Environment Using a Behavior-Based Neural Network Approach, Robotica, 37(1), 1–15.
]Search in Google Scholar
[
13. Protik P., Das S., Islam M. R. (2019, October). Chemical Reaction Optimization for Mobile Robot Path Planning. International Joint Conference on Computational Intelligence, Springer, Singapore, 191–203.10.1007/978-981-15-3607-6_15
]Search in Google Scholar
[
14. Quan Y., Ouyang H., Zhang C., Li S., Gao L. (2021), Mobile Robot Dynamic Path Planning Based on Self-adaptive Harmony Search Algorithm and Morphin Algorithm. IEEE Access, 10.1109/ACCESS.2021.309870610.1109/ACCESS.2021.3098706
]Search in Google Scholar
[
15. Singh N.H, Thongam K. (2018), Neural network-based approaches for mobile robot navigation in static and moving obstacles environments, Intelligent Service Robotics, 12(1), 55–67.10.1007/s11370-018-0260-2
]Search in Google Scholar
[
16. Specht D. F. (1991), A general regression neural network. IEEE transactions on neural networks, 2(6), 568–576.10.1109/72.9793418282872
]Search in Google Scholar
[
17. Teli T. A., Wani M. A. (2021), A fuzzy based local minima avoidance path planning in autonomous robots. International Journal of Information Technology, 13(1), 33-40.10.1007/s41870-020-00547-0
]Search in Google Scholar
[
18. Tripathy H. K., Mishra S., Thakkar H. K., Rai D. (2021), CARE: A Collision-Aware Mobile Robot Navigation in Grid Environment using Improved Breadth First Search. Computers & Electrical Engineering, 94, 107327.10.1016/j.compeleceng.2021.107327
]Search in Google Scholar
[
19. Wang M. (2021), Real-time path optimization of mobile robots based on improved genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 235(5), 646-651.10.1177/0959651820952207
]Search in Google Scholar
[
20. Zhao T., Xiang Y., Dian S., Guo R., Li S. (2020), Hierarchical interval type-2 fuzzy path planning based on genetic optimization, Journal of Intelligent & Fuzzy Systems, 32, 1-12.10.3233/JIFS-191864
]Search in Google Scholar
, 