AbsIracfAll mobile robots suffer from odometry error. Relative localization from odometry has both the systematic and the non-systematic errors. However, once a precise system error model and its parameters are given, the accuracy of odometry can be remarkably improved. Most previous works on this effort focused on the differential drive robots with little attention to the other types of mobile...

We evaluate the radio signal strength indicator (RSSI) of an nRF5188 based robot swarm for relative localization. We discuss an efficient way of high-speed data collection with up to 40,000 RSSI samples per second. Semi-automatic radio parameter selection as well as robot-assisted data collection methods are presented. Furthermore, we show our collected data including the variance for selected ...

All mobile bases suffer from localization errors. Previous approaches to accommodate for localization errors either use external sensors such as lasers or sonars, or use internal sensors like encoders. An encoder’s information is integrated to derive the robot’s position; this is called odometry. A combination of external and internal sensors will ultimately solve the localization error problem...