Deep Learning Based Path-Planning Using CRNN and A* for Mobile Robots
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-35308-6_10
Reference20 articles.
1. Guruji, A.K., Agarwal, H.,Parsediya, D.K.: Time-efficient A* algorithm for robot path planning. Procedia Technol. 23, 144–149 (2016). 3rd International Conference on Innovations in Automation and Mechatronics Engineering 2016, ICIAME 2016 05–06 February 2016. ISSN 2212-0173
2. Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybern. 4(2), 100–107 (1968). Publisher: IEEE
3. Algfoor, Z.A., Sunar, M.S., Kolivand, H.: A comprehensive study on pathfinding techniques for robotics and video games. Int. J. Comput. Games Technol. (2015)
4. Kala, R., Shukla, A., Tiwari, R., Rungta, S., Janghel, R.R.: Mobile robot navigation control in moving obstacle environment using genetic algorithm, artificial neural networks and A* algorithm. In: 2009 WRI World Congress on Computer Science and Information Engineering, vol. 4, pp. 705–713, IEEE (2009)
5. Tamar, A., Wu, Y., Thomas, G., Levine, S.,Abbeel, P.: Value iteration networks. arXiv preprint arXiv:1602.02867 (2016)
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