SLAM OR Simultaneous localization and mapping are a problem in computation geometry that helps update maps. It was first researched upon in s detailed manner in the year 1986. This also keeps track of an agent at the same time. SLAM algorithms are popularly found in self-driving cars, rovers to keep a check on planetary movements, and various other robots. There are also different types of SLAM algorithms. “Collaborative SLAM” helps to form 3d images by compounding images from more than one robot. There is also something known as the “audio-visual SLAM” that was originally designed for human-robot interaction.
ORB SLAM mono camera is one of the first real-time SLAM systems that is visual. This helps in visually studying and forming the maps for robot navigation and obstacle avoidance. Various search websites that use robots for their search algorithm need robot navigation as well. Optical vision is also used to view maps. Various computer algorithms and optical sensors are used to do this. Thus, it can be concluded that since robots are an important part of our lives, robot navigation and obstacle avoidance are very essential as well. that is because the robots need to navigate freely in their environment.