Bearing-only SLAM in Indoor Environments Using a Modified Particle Filter

The implementation of a particle filter (PF) for vision-based simultaneous localisation and mapping (SLAtvI) for a mobile robot in an unstructured indoor environment is presented in this paper. Variations to standard PF are proposed to remedy the sample impoverishment problem in bearing-only SLAM. A CCD camera mounted on the robot is used as the measuring device and image quality is incorporated into data association, PF update and map management. A passive path control strategy to maintain the accuracy of the SLAM process is also illustrated. Experimental results from an implementation using real-life data acquired from a Pioneer robot are included to demonstrate the effectiveness of our approach.