[1] Abed, M.S., Lutfy, O.F. and Al-Doori, Q. (2021) A Review on Path Planning Algorithms for Mobile Robots. Engineering and Technology Journal, 39(5A), 804-820.
[2] Caraveo, C., Valdez, F. and Castillo, O. (2016) Optimization of fuzzy controller design using a new bee colony algorithm with fuzzy dynamic parameter adaptation. Applied Soft Computing, 43, 131-142.
[3] Chen, Y., Liang, J., Wang, Y., Pan, Q., Tan, J. and Mao, J. (2020) Autonomous mobile robot path planning in unknown dynamic environments using neural dynamics. Soft Computing, 24(18), 13979-13995.
[4] Elmi, Z. and Efe, M. Ö. (2021) Online path planning of mobile robot using grasshopper algorithm in a dynamic and unknown environment. Journal of Experimental & Theoretical Artificial Intelligence, 33(3), 467-485.
[5] Ge, S.S. and Cui, Y.J. (2002) Dynamic motion planning for mobile robots using potential field method. Autonomous robots, 13(3),207-222.
[6] Juang, C.F., Lin, C.H. and Bui, T.B. (2018) Multiobjective rule-based cooperative continuous ant colony optimized fuzzy systems with a robot control application. IEEE transactions on cybernetics, 50(2), 650-663.
[7] Lin, X., Wang, C., Wang, K., Li, M. and Yu, X. (2021) Trajectory planning for unmanned aerial vehicles in complicated urban environments: A control network approach. Transportation Research Part C: Emerging Technologies, 128, 103120.
[8] Martínez, E.A.R., Caron, G., Pégard, C. and Alabazares, D.L. (2020) Photometric path planning for vision-based navigation. In 2020 IEEE International Conference on Robotics and Automation (ICRA), 9007-9013, IEEE.
[9] Mitchell, J.P., Bruer, G., Dean, M.E., Plank, J.S., Rose, G.S. and Schuman, C.D. (2017) NeoN: Neuromorphic control for autonomous robotic navigation. In 2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS), 136-142, IEEE.
[10] Mohanty, P.K. and Dewang, H.S. (2021) A smart path planner for wheeled mobile robots using adaptive particle swarm optimization. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 43(2), 1-18.
[11] Rahmaniar, W. and Rakhmania, A.E. (2022) Mobile Robot Path Planning in a Trajectory with Multiple Obstacles Using Genetic Algorithms. Journal of Robotics and Control (JRC), 3(1), 1-7.
[12] Rusu, P., Petriu, E.M., Whalen, T.E., Cornell, A. and Spoelder, H.J. (2003) Behavior-based neuro-fuzzy controller for mobile robot navigation. IEEE transactions on instrumentation and measurement, 52(4), 1335-1340.
[13] Sharma, K.D., Chatterjee, A. and Rakshit, A. (2018) Experimental study II: Vision-based navigation of mobile robots. In Intelligent Control, 243-280, Springer, Singapore.
[14] Tran, V.P., Garratt, M.A. and Petersen, I.R. (2021) Multi-vehicle formation control and obstacle avoidance using negative-imaginary systems theory. IFAC Journal of Systems and Control, 15, 100117.
[15] Uriol, R. and Moran, A. (2017) April. Mobile robot path planning in complex environments using ant colony optimization algorithm. In 2017 3rd international conference on control, automation and robotics (ICCAR), 15-21, IEEE.
[16] Van Den Berg, J., Stilman, M., Kuffner, J., Lin, M. and Manocha, D. (2009) Path planning among movable obstacles: a probabilistically complete approach. In Algorithmic Foundation of Robotics VIII, 599-614, Springer, Berlin, Heidelberg.
[17] Wu, Z., Chen, Y., Liang, J., He, B. and Wang, Y. (2021) ST-FMT*: A Fast Optimal Global Motion Planning for Mobile Robot. IEEE Transactions on Industrial Electronics.
[18] Zhang, Z., Zheng, L., Chen, Z., Kong, L. and Karimi, H.R. (2020) Mutualcollision-avoidance scheme synthesized by neural networks for dual redundant robot manipulators executing cooperative tasks. IEEE transactions on neural networks and learning systems, 32(3), 1052-1066.
[19] Zhao, R. and Lee, H.K. (2017) Fuzzy-based path planning for multiple mobile robots in unknown dynamic environment. Journal of Electrical Engineering and Technology, 12(2), 918-925.
[20] Zhou, Y., Hu, H., Liu, Y., Lin, S.W. and Ding, Z. (2020) A distributed method to avoid higher-order deadlocks in multi-robot systems. Automatica, 112, 108706.
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