Abstract
This paper presents a performance analysis of two open-source, laser scanner-based Simultaneous Localization and Mapping (SLAM) techniques (i.e., Gmapping and Hector SLAM) using a Microsoft Kinect to replace the laser sensor. Furthermore, the paper proposes a new system integration approach whereby a Linux virtual machine is used to run the open source SLAM algorithms. The experiments were conducted in two different environments; a small room with no features and a typical office corridor with desks and chairs. Using the data logged from real-time experiments, each SLAM technique was simulated and tested with different parameter settings. The results show that the system is able to achieve real time SLAM operation. The system implementation offers a simple and reliable way to compare the performance of Windows-based SLAM algorithm with the algorithms typically implemented in a Robot Operating System (ROS). The results also indicate that certain modifications to the default laser scanner-based parameters are able to improve the map accuracy. However, the limited field of view and range of Kinect's depth sensor often causes the map to be inaccurate, especially in featureless areas, therefore the Kinect sensor is not a direct replacement for a laser scanner, but rather offers a feasible alternative for 2D SLAM tasks.
Highlights
The Simultaneous Localization and Mapping (SLAM) technique is a subject of interest in mobile robotics studies
2D SLAM system may be preferred in certain applications, while still leveraging the Kinect’s 3D depth sensor to detect obstacles of variable shapes and sizes
The results proved that the designed system was able to achieve real-time SLAM operation even though it consists of multiple controllers, utilizes wireless connection and more importantly, made use of a virtual machine for SLAM computation
Summary
The Simultaneous Localization and Mapping (SLAM) technique is a subject of interest in mobile robotics studies. SLAM process was simulated repeatedly with different parameter settings, while observing any effect on the performance and accuracy of the final map Another contribution of this paper is the design of a system that utilized a Linux virtual machine in Windows to execute the real-time 2D SLAM algorithms. The laser scanner is generally better than the Kinect in terms of range and angle, the Kinect could be more effective as a navigation sensor since it is able to provide 3D views in a relatively fast sampling period. This aspect is very important in order to perform SLAM in a real environment where there exist objects of variable shape and size.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
