Multiple Waypoint Navigation for Mobile Robot Using Control Lyapunov-Barrier Function (CLBF)

Ridlho Khoirul Fachri, M. Z. Romdlony, M. R. Rosa
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Abstract

We implemented the Control Lyapunov-Barrier Function (CLBF) method on the Autonomous Mobile Robot (AMR) hardware using the inverse kinematics of four mecanum wheels. The CLBF method is used to obtain stability and safety in the system. The stability of the system is defined when the AMR is able to reach the specified equilibrium point and the safety of the system is defined when the AMR is able to avoid the existing unsafe state. Waypoint navigation is used to provide several points of equilibrium so that the robot can move to the desired coordinate points. In this paper, we do not use a local sensor such as an encoder, but use a global sensor, namely a camera, to read the coordinates of the AMR position. We use a microcontroller to receive the coordinates of the $x$ and $y$ positions of the BLOB detection. The test was carried out three times with each time testing through three waypoints and one predetermined unsafe state. This study resulted in the percentage value of the implementation success of 76.47%, this value is the result of a comparison of the path generated by the simulation with Matlab and the path from the AMR real plant.
基于控制Lyapunov-Barrier函数(CLBF)的移动机器人多路点导航
利用四个机械轮的逆运动学,在自主移动机器人(AMR)硬件上实现了控制Lyapunov-Barrier函数(CLBF)方法。采用CLBF方法获得系统的稳定性和安全性。当AMR能够达到指定的平衡点时,定义系统的稳定性;当AMR能够避免现有的不安全状态时,定义系统的安全性。路点导航用于提供几个平衡点,以便机器人可以移动到所需的坐标点。在本文中,我们不使用局部传感器(如编码器),而是使用全局传感器(即摄像机)来读取AMR位置的坐标。我们使用微控制器来接收BLOB检测的x和y位置的坐标。测试进行了三次,每次测试通过三个航路点和一个预定的不安全状态。本研究的实现成功率百分比值为76.47%,该值是将Matlab仿真生成的路径与AMR真实工厂的路径进行比较的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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