An Auto Obstacle Collision Avoidance System using Reinforcement Learning and Motion VAE
Author:
Funder
Electronics and Telecommunications Research Institute
Publisher
Korea Computer Graphics Society
Link
http://journal.cg-korea.org/download/download_pdf?doi=10.15701/kcgs.2024.30.4.1
Reference20 articles.
1. Hung Yu Ling, Fabio Zinno, George Cheng, and Michiel van de Panne. 2020. Character Controllers Using Motion VAEs. ACM Trans. Graph. 39, 4, Article 40 (July 2020), 12 pages. 10.1145/3386569.3392422
2. Xue Bin Peng, Glen Berseth, KangKang Yin, and Michiel van de Panne. 2017. DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning. ACM Trans. Graph. 36, 4, Article 41 (July 2017), 16 pages. DOI: 10.1145/3072959.3073602
3. Jaedong Lee, Jungdam Won, and Jehee Lee. 2018. Crowd Simulation by Deep Reinforcement Learning. In Proceedings of Motion, Interaction and Games, Limassol, Cyprus, November 8-10, 2018, 7 pages. DOI: 10.1145/3230744.3230782
4. V. Lumelsky and T. Skewis, “Incorporating range sensing in the robot navigation function,” IEEE Transactions on Systems Man and Cybernetics, vol. 20, pp. 1058 – 1068, 1990. 10.1109/21.59969
5. V. Lumelsky and Stepanov, “Path-planning srategies for a point mobile automaton amidst unknown obstacles of arbitrary shape,” in Autonomous Robots Vehicles, I.J. Cox, G.T. Wilfong (Eds), New York, Springer, pp. 1058 – 1068, 1990. 10.1007/978-1-4613-8997-2_27
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