ORB-SLAM2 is a powerful system for real-time simultaneous localization and mapping (SLAM) that can be used with various types of cameras. This includes monocular, stereo, and RGB-D cameras. The system is capable of map reuse, loop closing, and relocalization capabilities. It is designed to work with standard CPUs and can be used in a variety of environments - from small hand-held indoors sequences to drones that fly in industrial environments and cars that drive around a city.
What is SLAM?
Simultaneous localization and mapping (SLAM) is a computational problem that involves mapping and tracking the location of an agent in an unknown environment. The agent can be anything from a robot to a person or a vehicle. The agent moves around the environment and, with the help of sensors, builds or updates a map of the environment around it. At the same time, it keeps track of its own position within the map. SLAM has become an important research area in autonomous navigation, robotics, and computer vision.
Why is SLAM important?
SLAM is important because it enables machines to perceive and navigate in unknown environments. It has applications in various fields, such as robotics, augmented reality, and autonomous vehicles. For instance, robots equipped with SLAM can navigate indoor environments without human intervention, which is especially useful in dangerous or challenging situations. Similarly, autonomous vehicles need SLAM to be able to drive on roads they have never seen before.
ORB-SLAM2 Features
ORB-SLAM2 is a state-of-the-art SLAM system that has several features that make it stand out from other systems. Here are some of the features that make ORB-SLAM2 an excellent choice for solving the SLAM problem:
Real-time performance
ORB-SLAM2 works in real-time, which means that it generates a map and tracks the camera's location in real-time. This makes it possible to use ORB-SLAM2 in applications that require quick responses and continuous monitoring.
Works with different types of cameras
ORB-SLAM2 can work with different types of cameras, including monocular, stereo, and RGB-D cameras. This makes it a versatile system that can be used in various situations.
Map reuse
ORB-SLAM2 can reuse a map that it has created before. This means that if the system returns to an environment it has been to before, it can use the existing map to navigate the environment. This feature can save computation time and improve the accuracy of the system's location tracking.
Loop closing
ORB-SLAM2 can detect when it returns to a place it has been to before (i.e. a loop closure). This enables the system to correct errors in the map and improve the accuracy of the system's location tracking.
Relocalization
ORB-SLAM2 can relocalize itself even after it has lost track of its location. This feature is useful when the system has been moved or its surroundings have changed. Relocalization enables the system to resume mapping and tracking its location from where it left off.
Applications of ORB-SLAM2
ORB-SLAM2 has several applications in various fields:
Robotics
ORB-SLAM2 can be used in robots that require autonomous navigation in real-time. Robots equipped with ORB-SLAM2 can move around unknown environments without human intervention. This can be especially useful in tasks that are hazardous to humans, such as search and rescue missions or inspections of hazardous environments.
Autonomous vehicles
ORB-SLAM2 can be used in autonomous vehicles such as self-driving cars, drones, and unmanned aerial vehicles. The system can enable these vehicles to navigate unknown environments without human intervention. Autonomous vehicles equipped with ORB-SLAM2 can drive on roads they have never seen before, making them a step closer to being truly autonomous.
Augmented reality
ORB-SLAM2 can be used in augmented reality applications that require real-time tracking of the camera's location. Augmented reality applications such as Pokemon Go, Snapchat filters, and IKEA Place use real-time tracking to overlay digital content on the real world. ORB-SLAM2 can enable these applications to work accurately and efficiently.
ORB-SLAM2 is a complete SLAM system that can be used with various types of cameras in different environments. It has several features that make it stand out from other systems, including real-time performance, map reuse, loop closing, and relocalization. ORB-SLAM2 has applications in different fields, such as robotics, autonomous vehicles, and augmented reality. SLAM is an important research area that enables machines to perceive and navigate in unknown environments. ORB-SLAM2 is an excellent example of how SLAM can be applied in a practical way.
