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Glossary

This glossary provides definitions for key terms used throughout the textbook.

A

Action: In robotics, a specific behavior or movement executed by a robot to achieve a goal.

Adaptive Control: A control method that adjusts its parameters in real-time based on changing conditions or system behavior.

AI (Artificial Intelligence): The simulation of human intelligence processes by machines, especially computer systems.

Algolia: A search-as-a-service platform that provides search functionality for websites and applications.

API (Application Programming Interface): A set of protocols and tools for building software applications that specify how software components should interact.

B

Bipedal: Having two feet; relating to walking on two legs, as in humanoid robots.

Bipedal Locomotion: The act of walking on two legs, a key challenge in humanoid robotics.

C

CI/CD (Continuous Integration/Continuous Deployment): Practices that involve automatically building, testing, and deploying code changes.

Computer Vision: A field of artificial intelligence that trains computers to interpret and understand the visual world.

Control System: A system that manages, commands, directs, or regulates the behavior of other devices or systems.

D

Docusaurus: A static-site generator that helps create documentation websites with minimal setup.

Distributed System: A system in which components located on networked computers communicate and coordinate their actions by passing messages.

E

End-Effector: The device at the end of a robotic arm that interacts with the environment, such as a gripper or tool.

Embodiment: The physical form of an AI system, particularly relevant in robotics where AI is integrated with physical hardware.

F

Forward Kinematics: The use of joint parameters to compute the Cartesian position and orientation of the end-effector.

G

Gazebo: A 3D simulation environment for robotics that provides physics simulation and realistic rendering.

GitHub Actions: A continuous integration and continuous deployment (CI/CD) platform that allows you to automate your software development workflows.

Gripper: A device used to grasp and manipulate objects, typically found at the end of a robotic arm.

H

Hardware-in-the-Loop (HIL): A testing method that involves connecting real hardware to a simulation environment.

Humanoid Robot: A robot with physical characteristics that resemble the human body, typically having a head, torso, two arms, and two legs.

I

Inverse Kinematics: The mathematical process of calculating joint parameters from the desired end-effector position and orientation.

Isaac Sim: NVIDIA's robotics simulation application based on NVIDIA Omniverse.

Isaac ROS: NVIDIA's collection of hardware-accelerated perception and navigation packages for ROS 2.

K

Kinematics: The study of motion without considering the forces that cause the motion.

L

LLM (Large Language Model): A type of artificial intelligence model that can generate and understand human language based on training on large text datasets.

Localization: The process by which a robot determines its position in a known or unknown environment.

M

MDX: A format that allows you to write JSX (JavaScript XML) in Markdown documents, used in Docusaurus for interactive content.

Mermaid: A JavaScript-based diagramming and charting tool that renders Markdown-inspired text definitions to create and modify diagrams dynamically.

N

Nav2: The navigation stack for ROS 2, providing path planning and obstacle avoidance capabilities.

Node: In ROS, a process that performs computation. Nodes are combined together into a graph and communicate with one another using topics, services, or actions.

P

Perception: The ability of a robot to sense and interpret its environment using sensors like cameras, LiDAR, and IMUs.

Prismatic Joint: A joint that provides linear sliding movement between two bodies.

Python: A high-level programming language commonly used in robotics and AI development.

R

Revolute Joint: A joint that provides rotational movement between two bodies.

Robot Operating System (ROS): A flexible framework for writing robot software that provides services designed for a heterogeneous computer cluster.

ROS 2: The second generation of the Robot Operating System with improved architecture for real-world applications.

rclpy: The Python client library for ROS 2, providing APIs for creating ROS nodes and communicating with other nodes.

S

Sensor Fusion: The process of combining data from multiple sensors to improve the accuracy and reliability of information.

Simulation: The imitation of the operation of a real-world process or system over time.

SLAM (Simultaneous Localization and Mapping): The computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.

Socially Assistive Robot: A robot that provides assistance through social interaction rather than physical interaction.

T

Topic: In ROS, a named bus over which nodes exchange messages.

Trajectory Planning: The process of determining a path for a robot to follow to achieve a specific task.

U

URDF (Unified Robot Description Format): An XML format for representing a robot model in ROS, describing the robot's physical and visual properties.

Unity: A cross-platform game engine that can be used for creating realistic 3D simulations and visualizations.

V

VLA (Vision-Language-Action): A system that integrates visual perception, language understanding, and physical action for autonomous robot operation.

VSLAM (Visual Simultaneous Localization and Mapping): A technique for SLAM that uses visual sensors as the primary input.

W

Whisper: OpenAI's automatic speech recognition system that can transcribe and translate speech.

X, Y, Z

XYZ: Common notation for the three-dimensional coordinate system (X, Y, Z axes).