Enhancing Navigational Performance with Holistic Deep-Reinforcement-Learning
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-44851-5_5
Reference26 articles.
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2. Kästner, L., Cox, J., Buiyan, T., Lambrecht, J.: All-in-one: a drl-based control switch combining state-of-the-art navigation planners. In: International Conference on Robotics and Automation (ICRA), pp. 2861–2867 (2022)
3. Qian, K., Ma, X., Dai, X., Fang, F.: Socially acceptable pre-collision safety strategies for human-compliant navigation of service robots. Adv. Robot. 24(13), 1813–1840 (2010)
4. Kästner, L., Buiyan, T., Zhao, X., Jiao, L., Shen, Z., Lambrecht, J.: Towards deployment of deep-reinforcement-learning-based obstacle avoidance into conventional autonomous navigation systems. arXiv preprint arXiv:2104.03616 (2021)
5. Dugas, D., Nieto, J., Siegwart, R., Chung, J.J.: Navrep: unsupervised representations for reinforcement learning of robot navigation in dynamic human environments. arXiv preprint arXiv:2012.04406 (2020)
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