Research report · Research Prototype
OpenUWOC-AI: AI for Underwater Optical Wireless Communication
Communication-constrained autonomy prototype · 2026–Present
OpenUWOC-AI extends the portfolio beyond land robots by treating communication reliability as another uncertainty source for autonomous systems.
Abstract
Explore how AI methods can support underwater optical communication reliability, channel adaptation, and communication-aware autonomy.
Scientific question: How can autonomous systems reason about communication uncertainty when operating in degraded underwater channels?
Contribution: A research prototype connecting AI, channel reliability, and communication-constrained robotic operation.
Marked research artifact slot
Communication-aware autonomy architecture
Architecture figure slot for verified diagrams of modules, data flow, and software boundaries.
Marked research artifact slot
Channel state · reliability · adaptation
Pipeline slot for GIFs or animations that explain estimation, planning, perception, or evaluation steps.
Marked research artifact slot
Synthetic channel reliability timeline
Demo slot reserved for real project videos or synthetic demos that are explicitly labeled as synthetic.
Research questions
- How should channel uncertainty be represented for robotic decision making?
- Can AI-assisted adaptation improve communication robustness?
- How can communication constraints be visualized reproducibly?
Methods
Implementation status
Implemented
- Research framing
- Repository connection
- Simulation intent
Research prototype
- Channel-reliability visualization
- Synthetic communication degradation
Planned
- Baseline simulations
- Link-quality metrics
- Communication-aware planning connection
Experiments and metrics
Experiments
- Synthetic channel-degradation demo — planned
Metrics
- link reliability — planned
- packet error rate — planned
- adaptation latency — planned
Quantitative benchmark tables will be added only after reproducible experiments are available.
Limitations
- Quantitative claims are intentionally withheld until reproducible benchmark runs are available.
- Visual figures and GIFs are placeholders unless a project page explicitly states that an artifact is generated from real experiments.
Reproducibility plan
Experiment workflow
Each module is prepared to document configuration files, datasets, evaluation metrics, and repeated experiment runs before quantitative claims are shown.
Repository setup
Public repositories are linked when available. Private, planned, or incomplete repositories remain clearly labelled rather than being presented as finished systems.
Literature context
- Underwater optical wireless communication
- Communication-aware autonomy
- AI-assisted channel adaptation
Roadmap
- Create reproducible channel experiments
- Connect link uncertainty to autonomy decisions
- Add technical report scaffold