Q-learning-based unmanned aerial vehicle path planning with dynamic obstacle avoidance
Author:
Publisher
Elsevier BV
Subject
Software
Reference41 articles.
1. A deep reinforcement learning based method for real-time path planning and dynamic obstacle avoidance;Chen;Neurocomputing,2022
2. L. Yang, J. Qi, J. Xiao, X. Yong, A literature review of UAV 3D path planning, in: Proceeding of the 11th World Congress on Intelligent Control and Automation, 2014, pp. 2376–2381, http://dx.doi.org/10.1109/WCICA.2014.7053093.
3. F. Borrelli, D. Subramanian, A. Raghunathan, L. Biegler, MILP and NLP Techniques for centralized trajectory planning of multiple unmanned air vehicles, in: 2006 American Control Conference, 2006, p. 6, http://dx.doi.org/10.1109/ACC.2006.1657644.
4. A dynamic path planning approach for dense, large, grid-based automated guided vehicle systems;Fransen;Comput. Oper. Res.,2020
5. M. Kanehara, S. Kagami, J.J. Kuffner, S. Thompson, H. Mizoguhi, Path shortening and smoothing of grid-based path planning with consideration of obstacles, in: 2007 IEEE International Conference on Systems, Man and Cybernetics, 2007, pp. 991–996, http://dx.doi.org/10.1109/ICSMC.2007.4414077.
Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Dynamic path planning of autonomous bulldozers using activity-value-optimised bio-inspired neural networks and adaptive cell decomposition;Applied Soft Computing;2024-10
2. Collision-Free Path Planning for Multiple Drones Based on Safe Reinforcement Learning;Drones;2024-09-12
3. Cross-regional path planning based on improved Q-learning with dynamic exploration factor and heuristic reward value;Expert Systems with Applications;2024-09
4. Energy-Efficient Online Path Planning for Internet of Drones Using Reinforcement Learning;Journal of Sensor and Actuator Networks;2024-08-29
5. A Path-Planning Approach for an Unmanned Vehicle in an Off-Road Environment Based on an Improved A* Algorithm;World Electric Vehicle Journal;2024-05-29
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3