> For the complete documentation index, see [llms.txt](https://team488.gitbook.io/documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://team488.gitbook.io/documentation/welcome-to-vision-documentation.md).

# Welcome To Vision Documentation

Welcome to the **Team 488 Robotics Vision AI Documentation**. This guide explains how our vision AI systems work, including setup, configuration, and usage during competitions. It provides the technical details needed to understand and improve the system.

### Jump right in

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Probability Mapping</strong></td><td>Explore how the system calculates and visualizes object positions and probabilities on the field.</td><td></td><td></td><td><a href="/documentation/probability-mapping/quick-overview.md">Probability Mapping</a></td></tr><tr><td><strong>Simulation</strong></td><td>Learn how to test and refine vision AI systems in a controlled virtual environment.</td><td></td><td></td><td><a href="/documentation/simulation/quick-overview.md">Simulation</a></td></tr><tr><td><strong>XTABLES</strong></td><td>Learn why we use custom networking data systems for optimized performance.</td><td></td><td></td><td><a href="/documentation/xtables/quick-overview.md">XTABLES</a></td></tr><tr><td>XDASH</td><td>Explore XDASH, its features, and its role in managing the Vision Team's systems.</td><td></td><td></td><td><a href="/documentation/xdash/quick-overview.md">XDASH</a></td></tr><tr><td><strong>AI Models</strong></td><td>Understand the structure and training process of models used for object detection and recognition.</td><td></td><td></td><td><a href="/documentation/ai-models/quick-overview.md">AI Models</a></td></tr><tr><td><strong>Jetson Orin Nano</strong></td><td>Discover why we use the powerful Orin Nano Computers for enhanced performance.</td><td></td><td></td><td><a href="/documentation/jetson-orin-nano/quick-overview.md">Jetson ORIN Nano</a></td></tr><tr><td>Project Setup</td><td>Setup your development environment and install all dependencies.</td><td></td><td></td><td><a href="/documentation/getting-started/setup-environment-windows-linux.md">Setup Environment (Windows/Linux)</a></td></tr><tr><td><strong>A* Path Planning</strong></td><td>Learn how the A* algorithm finds optimal paths while avoiding obstacles in real-time.</td><td></td><td></td><td><a href="/documentation/a-path-planning/quick-overview.md">A* Path Planning</a></td></tr><tr><td><strong>Autonomous Navigation</strong></td><td>Explore how the robot autonomously navigates, avoids obstacles, and prioritizes goals in real-time.</td><td></td><td></td><td><a href="/documentation/autonomous-navigation/quick-overview.md">Autonomous Navigation</a></td></tr><tr><td><strong>Integrated Camera System</strong></td><td>Delve into the multi-camera setup that ensures full field coverage with precise object detection and tracking.</td><td></td><td></td><td><a href="/documentation/camera-system/quick-overview.md">Camera System</a></td></tr><tr><td><strong>AprilTag Localization</strong></td><td>Learn how AprilTag-based localization achieves sub-inch precision for accurate robot positioning in dynamic environments.</td><td></td><td></td><td><a href="/documentation/april-tag-localization/quick-overview.md">April Tag Localization</a></td></tr></tbody></table>