As far as robotics is concerned, that technology is pretty advanced. However, one major problem that experts face is mapping and localization as far as robotics are concerned. This is where SLAM comes to the rescue. In this article, we are going to take a look at the importance of simultaneous localization and mapping. Read on to find out more.
Introduction to SLAM
Basically, SLAM is a good alternative to GPS and works somewhat similarly. This technology guides robots so that they can be aware of the environment and move in the right direction while performing their functions. Although GPS is an effective mapping system, there are some hurdles in the way of its functionality.
Due to the limitations of GPS, experts now use simultaneous localization and mapping. This technology has proven to be a great alternative to GPS as it offers a lot of advantages.
Since robots feature memory banks that have huge capacities, they can continue to map their location using SLAM. Apart from this, GPS does not guarantee an accurate position of the robot. However, as far as positioning is concerned, SLAM is the best choice. It aligns sensor data on multiple levels for creating a map.
If you think that this alignment is not a big deal, you need to think again. The sensor data goes through alignment on a number of levels. This multi-level process makes use of a lot of algorithms. Since this type of processing is quite complex, it requires the power of today’s GPUs.
SLAM can help solve a lot of problems in the world of navigation and mapping. For example, this technology can help drones and robots find their way in a closed environment. This is especially more useful where GPS technology cannot work properly.
Actually, SLAM figures out and determines position and orientation for robots with respect to the objects in close proximity.