Enriched indoor environment map building using multi-sensor based fusion approach

Abstract

Intelligent Service Robot (ISR) has become increasingly noticed because of new devices and novel technologies that make ISR a truly handy human aid in areas like medical care, security patrol, tour guide and edutainment. Therefore, how to provide an applicable map for ISR to autonomously navigate inside a building for task execution becomes an imminent issue. This paper investigates an information enriched map constructed by the environment geometry from laser range finder and the indoor directive signs commonly seen in living/working environment from camera image. To implement this enriched map, multi-sensor fusion techniques are utilized for robust pose and sign estimations. Furthermore, an improved alignment technique is applied to reduce the computational complexity in a single Graph-SLAM process.