| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Jishan Li, Zhichao Deng, Yong Feng, Nianbo Li. Deep-Reinforcement-Learning-Based Joint Energy Replenishment and Data Collection Scheme for WRSN. Sensors (Basel, Switzerland). vol 24. issue 8. 2024-04-27. PMID:38676003. |
subsequently, the drl model multiobjective deep deterministic policy gradient (moddpg) is employed to control and optimize the uav instantaneous heading and speed, effectively planning uav hover points. |
2024-04-27 |
2024-04-29 |
Not clear |
| Chanjuan Liu, Jinmiao Cong, Guangyuan Liu, Guifei Jiang, Xirong Xu, Enqiang Zh. Boosting Reinforcement Learning via Hierarchical Game Playing With State Relay. IEEE transactions on neural networks and learning systems. vol PP. 2024-04-22. PMID:38648134. |
due to its wide application, deep reinforcement learning (drl) has been extensively studied in the motion planning community in recent years. |
2024-04-22 |
2024-04-26 |
Not clear |
| Xiaoran Kong, Yatong Zhou, Zhe Li, Shaohai Wan. Multi-UAV simultaneous target assignment and path planning based on deep reinforcement learning in dynamic multiple obstacles environments. Frontiers in neurorobotics. vol 17. 2024-02-06. PMID:38318422. |
in this article, the problem of multi-uav target assignment and path planning is formulated as a partially observable markov decision process (pomdp), and a novel deep reinforcement learning (drl)-based algorithm is proposed to address it. |
2024-02-06 |
2024-02-09 |
Not clear |
| Kabirat Bolanle Olayemi, Mien Van, Sean McLoone, Stephen McIlvanna, Yuzhu Sun, Jack Close, Nhat Minh Nguye. The Impact of LiDAR Configuration on Goal-Based Navigation within a Deep Reinforcement Learning Framework. Sensors (Basel, Switzerland). vol 23. issue 24. 2023-12-23. PMID:38139578. |
the cost function of collision avoidance and path planning is defined as the reward of the drl model. |
2023-12-23 |
2023-12-25 |
Not clear |
| Kabirat Bolanle Olayemi, Mien Van, Sean McLoone, Stephen McIlvanna, Yuzhu Sun, Jack Close, Nhat Minh Nguye. The Impact of LiDAR Configuration on Goal-Based Navigation within a Deep Reinforcement Learning Framework. Sensors (Basel, Switzerland). vol 23. issue 24. 2023-12-23. PMID:38139578. |
over the years, deep reinforcement learning (drl) has shown great potential in mapless autonomous robot navigation and path planning. |
2023-12-23 |
2023-12-25 |
Not clear |
| Kabirat Bolanle Olayemi, Mien Van, Sean McLoone, Stephen McIlvanna, Yuzhu Sun, Jack Close, Nhat Minh Nguye. The Impact of LiDAR Configuration on Goal-Based Navigation within a Deep Reinforcement Learning Framework. Sensors (Basel, Switzerland). vol 23. issue 24. 2023-12-23. PMID:38139578. |
these new fovs are trained to obtain collision avoidance and path planning drl models to validate the proposed method. |
2023-12-23 |
2023-12-25 |
Not clear |
| Xuanzhi Wang, Yankang Sun, Yuyang Xie, Jiang Bin, Jian Xia. Deep reinforcement learning-aided autonomous navigation with landmark generators. Frontiers in neurorobotics. vol 17. 2023-09-07. PMID:37674856. |
to shorten training time and prevent mobile robots from getting stuck and spinning around, we design a new robot autonomous navigation framework which combines the traditional global planning and the local planning based on drl. |
2023-09-07 |
2023-10-07 |
Not clear |
| Weiguo Liu, Zhiyu Xiang, Han Fang, Ke Huo, Zixu Wan. A Multi-Task Fusion Strategy-Based Decision-Making and Planning Method for Autonomous Driving Vehicles. Sensors (Basel, Switzerland). vol 23. issue 16. 2023-08-26. PMID:37631557. |
the main task based on drl decision-making planning and the auxiliary task based on image semantic segmentation were cross-fused, and part of the network was shared with the main task to reduce the possibility of model overfitting and improve the generalization ability. |
2023-08-26 |
2023-09-07 |
Not clear |
| Weiguo Liu, Zhiyu Xiang, Han Fang, Ke Huo, Zixu Wan. A Multi-Task Fusion Strategy-Based Decision-Making and Planning Method for Autonomous Driving Vehicles. Sensors (Basel, Switzerland). vol 23. issue 16. 2023-08-26. PMID:37631557. |
its performance was better than other drl algorithms in certain tasks, which improved the generalization ability of the vehicle decision-making planning algorithm. |
2023-08-26 |
2023-09-07 |
Not clear |
| Tianyu Xing, Xiaohao Wang, Kaiyang Ding, Kai Ni, Qian Zho. Improved Artificial Potential Field Algorithm Assisted by Multisource Data for AUV Path Planning. Sensors (Basel, Switzerland). vol 23. issue 15. 2023-08-12. PMID:37571463. |
the improved artificial potential field (iapf) method is combined with drl for path planning while optimizing the reward function in the drl algorithm and using the generated path to optimize the future path. |
2023-08-12 |
2023-08-16 |
Not clear |
| Yahao Xu, Yiran Wei, Di Wang, Keyang Jiang, Hongbin Den. Multi-UAV Path Planning in GPS and Communication Denial Environment. Sensors (Basel, Switzerland). vol 23. issue 6. 2023-03-30. PMID:36991708. |
this paper proposes a feature fusion proximal policy optimization (ff-ppo) algorithm based on deep reinforcement learning (drl); the algorithm can fuse image recognition information with the original image, realizing the multi-uav path planning algorithm without an accurate target location. |
2023-03-30 |
2023-08-14 |
Not clear |
| Shunsuke Koseki, Kyo Kutsuzawa, Dai Owaki, Mitsuhiro Hayashib. Multimodal bipedal locomotion generation with passive dynamics Frontiers in neurorobotics. vol 16. 2023-02-09. PMID:36756534. |
by carefully planning the weight parameter settings of the drl reward function during the learning process based on a curriculum learning method, the bipedal model successfully learned to walk, run, and perform gait transitions by adjusting only one command input. |
2023-02-09 |
2023-08-14 |
Not clear |
| I-Ju Chen, Markus Aapro, Abraham Kipnis, Alexander Ilin, Peter Liljeroth, Adam S Foste. Precise atom manipulation through deep reinforcement learning. Nature communications. vol 13. issue 1. 2022-12-05. PMID:36470857. |
the drl agent learns to manipulate ag adatoms on ag(111) surfaces with optimal precision and is integrated with path planning algorithms to complete an autonomous atomic assembly system. |
2022-12-05 |
2023-08-14 |
Not clear |
| Lanyu Xu, Simeng Zhu, Ning We. Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey. Physics in medicine and biology. 2022-10-21. PMID:36270582. |
drl is an active research area with enormous potential to improve deep learning applications in medical imaging and radiation therapy planning. |
2022-10-21 |
2023-08-14 |
Not clear |
| Lanyu Xu, Simeng Zhu, Ning We. Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey. Physics in medicine and biology. 2022-10-21. PMID:36270582. |
this paper introduces the basics of reinforcement learning and reviews various categories of drl algorithms and drl models developed for medical image analysis and radiation treatment planning optimization. |
2022-10-21 |
2023-08-14 |
Not clear |
| Lienhung Chen, Zhongliang Jiang, Long Cheng, Alois C Knoll, Mingchuan Zho. Deep Reinforcement Learning Based Trajectory Planning Under Uncertain Constraints. Frontiers in neurorobotics. vol 16. 2022-05-19. PMID:35586262. |
with the advance in algorithms, deep reinforcement learning (drl) offers solutions to trajectory planning under uncertain environments. |
2022-05-19 |
2023-08-13 |
human |
| Lienhung Chen, Zhongliang Jiang, Long Cheng, Alois C Knoll, Mingchuan Zho. Deep Reinforcement Learning Based Trajectory Planning Under Uncertain Constraints. Frontiers in neurorobotics. vol 16. 2022-05-19. PMID:35586262. |
finally, our final report shows the effectiveness of state-of-the-art drl algorithms for trajectory planning under uncertain environments with zero collision after 5,000 episodes of training. |
2022-05-19 |
2023-08-13 |
human |
| Lienhung Chen, Zhongliang Jiang, Long Cheng, Alois C Knoll, Mingchuan Zho. Deep Reinforcement Learning Based Trajectory Planning Under Uncertain Constraints. Frontiers in neurorobotics. vol 16. 2022-05-19. PMID:35586262. |
different from traditional trajectory planning which requires lots of effort to tackle complicated high-dimensional problems, the recently proposed drl enables the robot manipulator to autonomously learn and discover optimal trajectory planning by interacting with the environment. |
2022-05-19 |
2023-08-13 |
human |
| Damon Sprouts, Yin Gao, Chao Wang, Xun Jia, Chenyang Shen, Yujie Ch. The development of a deep reinforcement learning network for dose-volume-constrained treatment planning in prostate cancer intensity modulated radiotherapy. Biomedical physics & engineering express. 2022-05-06. PMID:35523130. |
in this work, we show an end-to-end study to train a deep reinforcement learning (drl) based virtual treatment planner (vtp) that can behave like a human to operate a dose-volume constrained treatment plan optimization engine following the parameters used in eclipse tps for high-quality treatment planning. |
2022-05-06 |
2023-08-13 |
human |
| Reeve Lambert, Jianwen Li, Li-Fan Wu, Nina Mahmoudia. Robust ASV Navigation Through Ground to Water Cross-Domain Deep Reinforcement Learning. Frontiers in robotics and AI. vol 8. 2021-10-08. PMID:34616776. |
this is done by integrating a drl agent at a high level of vehicle control and leveraging existing path planning and proven low-level control methodologies that are utilized in multiple domains. |
2021-10-08 |
2023-08-13 |
Not clear |