Concurrent indoor map construction and patterns of interests recognition using sensory fusion approach for service robotics

It is desirable that an Intelligent Service Robot (ISR) will not only construct the environment map but also recognize the meaningful symbols/signs in the building it services simultaneously. The objective of this paper is to describe an ISR autonomously estimate the environment structure and simultaneously detect the commonly recognized symbols/signs in the building. The result is an information map constructed by the environment geometry from a laser range finder and the indoor indicators from visual image. To implement this indicative information map, sensory fusion techniques: batch Maximum Likelihood Estimator (MLE) and Covariance Union (CU) are tactically utilized for robust pose and sign estimations in a single SLAM process. Also, a 2.5D indicative environment map has been constructed rapidly with the 3D Mesa SwissRanger. We have successfully demonstrated the proof of concept experimentally and summarized in the concluding remarks.