UACOF: A USV-AUV Collaboration Framework for Underwater Tasks Under Extreme Sea Conditions (Student Abstract)

Authors

  • Jingzehua Xu Massachusetts Institute of Technology
  • Guanwen Xie Massachusetts Institute of Technology
  • Yimian Ding Massachusetts Institute of Technology
  • Yongming Zeng Zhejiang University
  • Haoyu Wang Zhejiang University
  • Shuai Zhang New Jersey Institute of Technology

DOI:

https://doi.org/10.1609/aaai.v39i28.35317

Abstract

Ocean exploration requires effective collaboration between the unmanned surface vehicle (USV) and autonomous underwater vehicles (AUVs). We propose UACOF, a USV-AUV collaboration framework that enhances multi-AUV performance under extreme sea conditions. The framework includes high-precision multi-AUV location via USV path planning with Fisher information matrix optimization and reinforcement learning training for cooperative tasks. Experimental results show UACOF's superior feasibility, performance, coordination and robustness in extreme conditions.

Published

2025-04-11

How to Cite

Xu, J., Xie, G., Ding, Y., Zeng, Y., Wang, H., & Zhang, S. (2025). UACOF: A USV-AUV Collaboration Framework for Underwater Tasks Under Extreme Sea Conditions (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 39(28), 29538–29540. https://doi.org/10.1609/aaai.v39i28.35317