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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.