Dynamic Optical Localization of a Mobile Robot Using Kalman Filtering-Based Position Prediction
Jason N. Greenberg, Xiaobo Tan
Abstract
Autonomous mobile robots operating in areas with poor GPS and wireless coverage (e.g., underwater) must rely on alternative localization and communication approaches. In this article, we present an light-emitting diode (LED) based system that achieves simultaneous localization and communication (SLAC), where the line-of-sight (LOS) requirement for communication is exploited to extract the relative bearing of the communicating parties for localization. By using Kalman filtering to obtain the mobile robot's predicted position, the system is able to reduce the overhead of establishing the LOS and, therefore, significantly improve on the quality of the localization. The proposed design of the optical localization system is presented and its effectiveness is demonstrated with extensive simulation and experimentation in a two-dimensional setting, consisting of a mobile robot and two stationary base nodes.