Multi-Head PPO-Based Path Planning for AUV Data Collection under Dynamic Ocean Currents

  • Kim, Minho
  • Seol, Seunghwan
  • Lee, Samghwa
  • Kim, Yongcheol
  • Chung, Jaehak
Citations

SCOPUS

0

초록

This paper proposes a reinforcement learning- based path planning framework for autonomous underwater vehicle (AUV) data collection in dynamic ocean currents, simultaneously considering propulsion and communication energy, buffer capacity, and Age of Information (AoI). By employing a multi-head PPO network, the method jointly learns node selection and velocity control. Simulation results indicate that the proposed approach outperforms the greedy baseline in energy efficiency and mission success rate, with approximately 12% higher offloading efficiency and 11% lower AoI. © 2026 IEEE.

키워드

Age of InformationAutonomous Underwater VehiclePath PlanningPPOReinforcement LearningUnderwater Sensor Network
제목
Multi-Head PPO-Based Path Planning for AUV Data Collection under Dynamic Ocean Currents
저자
Kim, MinhoSeol, SeunghwanLee, SamghwaKim, YongcheolChung, Jaehak
DOI
10.1109/ICEIC69189.2026.11385932
발행일
2026
유형
Conference paper
저널명
2026 International Conference on Electronics, Information, and Communication, ICEIC 2026