Comparison of Rough Mereology Based Path Planning Algorithms for Intelligent Robotics
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-30275-7_30
Reference16 articles.
1. Adamu, P.I., Okagbue, H.I., Oguntunde, P.E.: Fast and optimal path planning algorithm (FAOPPA) for a mobile robot. Wirel. Pers. Commun. (2019). https://doi.org/10.1007/s11277-019-06180-w
2. Li, B., Liu, H., Su, W.: Topology optimization techniques for mobile robot path planning. Appl. Soft Comput. J. 78, 528–544 (2019). https://doi.org/10.1016/j.asoc.2019.02.044
3. Low, E.S., Ong, P., Cheah, K.C.: Solving the optimal path planning of a mobile robot using improved Q-learning. Robot. Auton. Syst. 115, 143–161 (2019). https://doi.org/10.1016/j.robot.2019.02.013
4. Moradi, B.: Multi-objective mobile robot path planning problem through learnable evolution model. J. Exp. Theor. Artif. Intell. 31(2), 325–348 (2019). https://doi.org/10.1080/0952813X.2018.1549107
5. de Oliveira, G.C.R., de Carvalho, K.B., Brandão, A.S.: A hybrid path-planning strategy for mobile robots with limited sensor capabilities. Sensors (Basel, Switzerland) 19(5) (2019). https://doi.org/10.3390/s19051049
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