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How to Use This Glossary

Content Levels

Each entry is tagged with a level indicating the type of content:

ConceptualPracticalDeep Dive

Conceptual

Theory and foundational understanding. Answers “what is this?” and “why does it matter?”

Examples: Kinematics, Degrees of Freedom, Coordinate Frames

Practical

Hands-on, how-to content. Answers “how do I use this?” with code, setup guides, and workflows.

Examples: Jetson Thor, ROS 2, Isaac ROS, DGX Spark

Deep Dive

Comprehensive, in-depth coverage. Goes beyond basics into architecture, algorithms, and advanced usage.

Examples: SLAM (full pipeline breakdown), Motion Planning algorithms

Site Organization

The glossary is organized by domain:

Concepts

Theoretical foundations that underpin robotics:

  • Fundamentals — Core concepts (kinematics, DOF, transforms)
  • Perception — How robots sense the world (SLAM, vision, sensor fusion)
  • Control & Planning — How robots decide and act
  • AI & Learning — Machine learning for robotics

Hardware

Physical compute platforms and components:

  • Compute Platforms — Jetson Thor, Jetson Orin, DGX Spark
  • Sensors — Cameras, LiDAR, IMU
  • Actuators — Motors, servos, grippers

Software

Tools, frameworks, and platforms:

  • Frameworks — ROS 2 and middleware
  • Isaac Platform — NVIDIA’s robotics software stack
  • Simulation — Isaac Sim, Gazebo
  • SDKs & Tools — TensorRT, cuDNN, etc.

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Every term links to related concepts. Follow your curiosity.

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Callout Types

Throughout the glossary, you’ll see colored callout boxes:

  • Note (blue): Additional context or background
  • Tip (green): Best practices and recommendations
  • Caution (yellow): Important warnings
  • Danger (red): Critical information about potential issues

Contributing

Found an error? Want to add a term? See our contribution guide.