Abstract
This article is concerned with the solution of the SLAM (Simultaneous Localization And Mapping) problem in an indoor environment using a low-cost mobile robot. The robot was constructed with a distance measurement sub-system composed of three types of sensors: a wireless webcam with a laser pointer (a visual sensor), two infrared sensors and an ultrasonic TOF (time-of-flight) sensor. An algorithm is proposed to fuse the noisy data provided by these sensors and a particle filter approach is employed to solve the SLAM problem. The proposed fusion algorithm was evaluated using two artificial indoor environments and the estimated maps were used to navigate the robot satisfactorily in these environments.
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