Autonomous Exploration of Complex Underwater Environments Using a Probabilistic Next-Best-View Planner-Reference-Cited by-同舟云学术

Autonomous Exploration of Complex Underwater Environments Using a Probabilistic Next-Best-View Planner

Published:2019-04 Issue:2 Volume:4 Page:1619-1625
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Palomeras Narcis^ORCID,Hurtos Natalia^ORCID,Vidal Eduard^ORCID,Carreras Marc^ORCID

Funder

Spanish national Ministerio de Economía y Compet

Spanish national project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/8581687/08630631.pdf?arnumber=8630631

Cited by 38 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. Adaptive energy-efficient reinforcement learning for AUV 3D motion planning in complex underwater environments;Ocean Engineering;2024-11

2. Input-Quantized Output Feedback Control for Autonomous Underwater Vehicles with Tunnel Prescribed Performance;2024 36th Chinese Control and Decision Conference (CCDC);2024-05-25

3. Heuristic Based Online Information Path Planning;2024 36th Chinese Control and Decision Conference (CCDC);2024-05-25

4. Real-Time Planning Under Uncertainty for AUVs Using Virtual Maps;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. Minimax Rao-Blackwellized Particle Filtering in 2D LIDAR SLAM;International Journal of Control, Automation and Systems;2024-04-26