Multisensor based effective indoor environment map build-up for intelligent service robot

Intelligent Service Robot (ISR) has become increasingly noticed because of new devices and novel technologies that advance ISR to be true handy human aids 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 essential issue. This paper investigates a consistent map consists of environment geometry by laser rangefinder. The Covariance Intersection (CI) method is utilized to fuse the robot pose for a robust estimation from wheel encoder and laser scan match. Simultaneously, a 2.5D environment structure map can be constructed rapidly with the Mesa SwissRanger. Finally, a consistent environment map in a unitary localization and mapping process via the sensory fusion and optimal alignment methodology has been constructed and implemented successfully.

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