Simultaneous Localization and Mapping (SLAM) is a technique used by autonomous systems, such as robots and self-driving vehicles, to construct a map of an unknown environment while simultaneously determining their position within that map. This dual process enables these systems to navigate and understand their surroundings without prior knowledge of the environment.
Key Components of SLAM:
- Localization: Determining the system’s position and orientation within the environment.
- Mapping: Creating a representation of the environment’s features, such as obstacles and landmarks.
Applications of SLAM:
- Robotics: Enables robots to autonomously navigate and perform tasks in unknown environments.
- Autonomous Vehicles: Allows self-driving cars to understand and navigate complex roadways.
- Augmented Reality (AR): Facilitates the overlay of digital information onto the physical world by accurately mapping the environment.