3 articles tagged with #underwater-robotics. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers developed a constrained reinforcement learning approach for underwater vehicle control that explicitly budgets thruster power consumption, reducing energy use by 14-65% compared to traditional methods without requiring manual tuning for each vehicle or task.
Researchers propose LASSA, an LLM-based autonomous control architecture for unmanned underwater vehicles that combines large language models with physical constraint verification to enable fault-tolerant operation in communication-limited environments. Lake experiments demonstrate the system successfully detects faults, replans missions, and maintains operational safety without false alarms.
Lincoln Laboratory intern Ivy Mahncke developed and tested algorithms designed to assist human divers and robots with underwater navigation. This research represents advancement in underwater robotics and navigation technology applications.
