ALF: An autonomous localization framework for self-localization in indoor environments

A lot of algorithms and applications can benefit from position information. GPS localization has become a standard for outdoor usage. But if a higher accuracy is needed or within GPS-denied areas providing this knowledge is still an open and nontrivial topic. Especially for unknown or dynamic environments. In this paper we propose a framework which is capable of autonomously exploring unknown environments in a fully decentralized way. It provides accurate and real-time localization support for customers. The usual very time intensive manual deployment and position assignment of reference nodes is avoided. Additional we show that the algorithm can detect and handle Non Line of Sight (NLOS) issues which is a very important criteria for real world applications.