In addition, since cameras provide a large volume of information, they can be used to detect landmarks (previously measured positions). Visual SLAM can be implemented at low cost with relatively inexpensive cameras. Visual SLAM can use simple cameras (wide angle, fish-eye, and spherical cameras), compound eye cameras (stereo and multi cameras), and RGB-D cameras (depth and ToF cameras). Visual SLAMĪs the name suggests, visual SLAM (or vSLAM) uses images acquired from cameras and other image sensors. To learn more about the front-end processing component, let’s take a look at visual SLAM and lidar SLAM – two different methods of SLAM.
The robot can also simultaneously use the camera and other sensors to create a map of the obstacles in its surroundings and avoid cleaning the same area twice. On the other hand, robots with SLAM can use information such as the number of wheel revolutions and data from cameras and other imaging sensors to determine the amount of movement needed. In addition, this approach uses excessive power, so the battery will run out more quickly. Without SLAM, it will just move randomly within a room and may not be able to clean the entire floor surface. SLAM ExamplesĬonsider a home robot vacuum. To understand why SLAM is important, let's look at some of its benefits and application examples. But with vast improvements in computer processing speed and the availability of low-cost sensors such as cameras and laser range finders, SLAM is now used for practical applications in a growing number of fields. SLAM has been the subject of technical research for many years.
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