What Is Autonomous Navigation?

Autonomous navigation enables robots to move and make decisions independently using onboard sensors and software.

Line Following Robots

Line following robots use infrared (IR) sensors to stay on a designated path marked by contrasting colors.

How It Works

This section provides insights into the mechanisms of autonomous navigation, focusing on how robots detect lines and avoid obstacles using sensors.

Basic Logic

This section focuses on basic logic programming structures used in autonomous navigation robots.

Obstacle Avoidance

Obstacle avoidance is a key component of autonomous navigation in robots, enabling them to detect and navigate around obstacles utilizing sensors.

Sensors Used

This section discusses the various sensors used for obstacle avoidance in robots.

Example

Path Planning (Intro)

Path planning is essential for determining the most efficient route from a starting point to a destination using various algorithms.

Algorithms

This section covers the concept of algorithms in the context of autonomous navigation, including their role in robotic path planning and decision-making.

Localization And Mapping (Basic Overview)

This section introduces the concepts of localization and mapping in autonomous robots, highlighting their importance and applications.

Slam (Simultaneous Localization And Mapping)

SLAM is a technique that enables robots to simultaneously map their environment while keeping track of their own location.

Real-World Applications

This section highlights various real-world applications of autonomous navigation technologies.