Panoramic vision and LRF sensor fusion based human identification and tracking for autonomous luggage cart

In this paper, we propose a solution for human identification and localization with a mobile robot problem that implements multi-sensor data fusion techniques. This solution is designed for an autonomous luggage cart. The system utilizes a new approach based on identifying the target human visually from an omni directional camera then localizing and tracking him using LRF. This approach is composed of "Registration Stage" and "Identification and Localization Stage". The registration stage extracts all necessary information needed including patches from the clothes. The identification is made using a modified pattern-matching algorithm to fit to a real time application. The tracking is implemented using a positions history structure to keep record of all positions of surrounding objects and the identified human. We implemented the proposed approach in fixed configuration to test its effectiveness.