Improving performance of 2D SLAM methods by complementing Kinect with laser scanner

The feasibility of using Kinect sensor for 2D Simultaneous Localization and Mapping (SLAM) application has been widely studied. Researchers concluded that the acquired maps are often inaccurate due to the limited field of view of the sensor. Therefore in this work, we complemented the Kinect with a laser scanner and proposed a method to merge the data from both sensors. Two SLAM algorithms (i.e Gmapping and Hector SLAM) were tested using the method, in different environments. The results show that the method is able to detect multi-sized objects and produce more accurate map as compared to when using single sensor (i.e Kinect only or laser scanner only). Finally, the performance of the Gmapping and Hector SLAM are compared particularly in terms of the computational complexity and the map accuracy.