ANCHOR Glider Command: Browser-based AUV Glider Mission Planning Sandbox and Serious Game

ANCHOR Glider Command is a browser-based AUV glider mission planning simulator built with Phaser 3 and vanilla JavaScript. It integrates computational science and gamification design, serving both as a serious game and a research sandbox. It supports deterministic/stochastic multi-agent mission planning, ocean current simulation, path optimization, and external solver integration, which can be used for scientific algorithm validation and conceptual demonstration in teaching scenarios.

Autonomous Underwater Vehicle (AUV) gliders are important tools for marine scientific research, with advantages of low energy consumption and long endurance (several months), suitable for large-scale ocean data collection. However, their mission planning faces unique challenges: ocean currents significantly affect trajectories, energy management is crucial, and the timing of surfacing determines the window for data transmission and re-planning. Planners need to balance complex environments, limited energy, and mission objectives. This project transforms this scientific problem into an interactive browser game to serve research and teaching.

Project Positioning

The project is a "browser-first AUV glider planning puzzle game and model-driven simulator" with dual attributes:

• Serious game: Used for teaching long-cycle planning, energy trade-offs, waypoint sorting, prediction uncertainty, etc.
• Research sandbox: Supports multi-agent mission planning, surfacing decisions, re-planning, and external solver workflows

Technical Architecture

Uses a pure front-end tech stack, zero dependencies for out-of-the-box use:

• Game engine: Phaser 3 (loaded from local vendor directory)
• Front-end tech: Vanilla JavaScript, HTML, CSS
• Deployment: Hosted on static file servers; can be launched locally via python -m http.server 8000
• Optional dependency: Playwright for development testing

Scene System

Includes complete workflow: Main menu (with Demo), mission briefing, planning scene (waypoint placement/timeline editing), simulation scene, mission summary, level editor, dataset export

Planning Workspace

Three-column layout: Left task console (menu/form/import-export), central simulation viewport (Phaser-rendered map/animation), right waypoint timeline

Ocean Current Simulation System

• Seed-based parameterized presets
• Supports static/dynamic (time-varying) current fields
• Multiple evolution behaviors: Continuous, cyclic, single pulse, meandering movement
• Real-time preview and statistics

Teaching Mode

14 phased tutorials: Basic waypoint operations, current path planning, energy management, multi-glider collaboration, stochastic scenarios, etc.

Core Gameplay Loop

Select level → Configure parameters → Read mission briefing → Place waypoints → Execute simulation → View score → Retry/Export data

Scoring and Target System

• Sequential gold star targets: Time-limited high-value targets
• ROI hotspots: Dynamically changing data collection areas
• Hazardous areas: Areas to avoid
• Energy budget: Limits total movement distance

Planning Auxiliary Tools

Guidance cone (suggested heading), reachable range preview (energy/current prediction), predicted surfacing position, waypoint stacking in the same grid

External Solver Integration

• Export standardized JSON data packages (level configuration/current field/mission objectives)
• Supports external planning import and verification
• Provides Python example solvers and JavaScript headless tools

Value Applications

• Educational scenarios: Operations research course demonstrations, oceanography introduction, algorithm visualization
• Research applications: Algorithm comparison, batch generation of test datasets, human-machine collaboration research

Version Evolution

Currently at Version 2, with improvements including: Responsive layout, collapsible console, local storage of interface state, debugging tools, browser-based local leaderboard

Project Significance

This project transforms complex scientific computing into an interactive experience, serving as a bridge between operations research algorithms and marine applications. For educators, it is an out-of-the-box teaching tool; for researchers, it is an extensible algorithm verification platform; for enthusiasts, it is a science popularization strategy game. The open-source and zero-dependency features lower the barrier to use, promoting the development of the AUV mission planning field.