Positioning and Trajectory Tracking for Caterpillar Vehicles in Unknown Environment
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ISSN:1598-6446 eISSN:2005-4092 http://www.springer.com/12555
Positioning and Trajectory Tracking for Caterpillar Vehicles in Unknown Environment Van Lanh Nguyen, Dae Hwan Kim, Van Sy Le, Sang Kwun Jeong, Choong Hwan Lee, Hak Kyeong Kim, and Sang Bong Kim* Abstract: This paper proposes positioning and trajectory tracking for Caterpillar Vehicles (CVs) in unknown environments. To do these tasks, the following are performed. Firstly, a system modeling of the Caterpillar Vehicle is presented. Secondly, solving the complicated tracking control problem in unknown environments is a challenging mission. Therefore, to guarantee the Caterpillar Vehicle system to be strong robustness against external disturbances in the unknown environments, a MIMO robust servo controller for tracking the desired trajectory is designed by using a Linear Shift Invariant Differential (LSID) operator. The CVs are able to accomplish various tasks in dangerous places where workers cannot enter. Thirdly, the positioning of the CV can be obtained using a Simultaneous Localization and Mapping (SLAM) method. This paper develops perfectly the SLAM algorithm for positioning of the CV based on laser sensor Lidar. The main advantage of this method is that it does not need to use more landmarks. Landmarks can be obtained from the unknown environment. Thus, the CV can work even in unknown environments and unsafe places. Finally, to verify the effectiveness of the proposed MIMO robust servo controller and the SLAM positioning algorithm, the experimental results are presented. The experimental results demonstrate the adequate tracking performance of the proposed MIMO robust servo controller in the unknown environment. Keywords: CV, EKF, LSID operator, MIMO, robust servo controller, SLAM.
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INTRODUCTION
In recent years, autonomous robots are commonly used in factories due to its potential wide applications in transportation and dangerous tasks. Such mobile robots can be used in applications that include delivering components between stations in factories, delivering food, and medication in hospitals, cleaning the rooms, or agricultural tasks. Some applications may take place in dangerous environments, for example, nuclear waste facilities, and sites with harmful gases or high temperatures. And mobile robots can work in unsafe environments where workers cannot enter. A trajectory tracking control problem is one of the key techniques in mobile robot research. Several types of research have been implemented and various control methods have been proposed for the trajectory tracking of mobile robots. Gomes et al. [1] proposed a PID controller for trajectory tracking of mobile robots. Yuan et al. [2]
proposed another control method such as fuzzy control. Hung et al. [3] proposed the sliding mode controller design for mobile robots. Pratama et al. [4] proposed a backstepping control method to track the trajectory. Feng et al. [5] proposed a model reference adaptive control method for the differential drive mobile robot. However, most of the previous methods hav
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