Simultaneous Location and Mapping (SLAM) is the computational problem of creating a map of an unknown area while simultaneously maintaining knowledge of an object’s position within it. Wireless SLAM leverages existing Wi-Fi/Bluetooth infrastructure, by mapping Wi-Fi access points and BLE beacons into a fingerprint database. It has been widely used in outdoor environments for GPS+ positioning, self-driving cars and domestic and industrial robots. But existing wireless SLAM technologies doesn’t have the level of accuracy for indoor use. It also requires lots of manual work to map. WiTagg has developed an easy to use, low cost SLAM solution called WiSLAM to deliver high accuracy indoor positioning.
WiTagg’s WiSLAM Signal Scanner gathers data from multitudes of Wi-Fi devices either by war-walking or war-driving in any area where Wi-Fi signals are present. WiSense Scanner uses patented techniques and Angle of Arrival principles to accurately locate and map the location of any unknown Wi-Fi APs and BLE beacons.
The fine-grain scanner comes with a long range smart antenna array that is able to capture wireless signals up-to 300 feet away. The patent-pending signal process algorithm is able to estimate the direction of the devices sending signals within one-degree accuracy and construct a wireless spatial map with few simple steps. It can work at non-line-of-sight environments, where there are walls and other types of obstruction. The procedure takes a fraction of time compared with other SLAM technology.
The inclusion of SLAM technologies in WiSLAM adaptive learning system for indoor positioning results in more accurate location information (X,Y,Z) deeper inside the building. It can be used by Smartphone, Automated Guided Vehicle/Robot, AR/VR and IoT applications.