The scope of the LOMAR project is to develop a robust general method for indoor localization and mapping based on intelligent algorithms and models and involving a robotic platform. The targeted objectives is to develop a method with the following outstanding characteristics:

• data acquisition is enhanced from manual to an automated process using a robotic platform;
• the hardware worn by the final end users is kept to a minimum, e.g. small tags, or even to common daily used devices such as smartphones;
• it operates as much as possible in an unsupervised way (least number of initial assumptions on the layout of the setup);
• it involves novel approach of human-machine collaboration.

The estimated results of the LOMAR project are:

• We will identify technologies and methods available for indoor localization as well as neural networks architectures suitable for fingerprint based localization with noisy fingerprints;
• we will develop and implement novel intelligent algorithms for indoor localization and will port these algorithms on a robotic platform;
• we will test and validate the developed method in a realistic scenario based on “person following”.