Abstract
The applications of mobile robots in rescue scenarios, surviving to search, and exploration for outdoor navigation have received increasing attention due to their promising prospects. In this paper, a simulation of a differential wheeled mobile robot was presented, implementing a Global Positioning System (GPS) data points to specified starting points, final destination, and total error.
 In this work, a simple kinematic controller for polar coordinate trajectory tracking is developed. The tracking between two points, pose to pose, was specified by using the GPS data points. After that, the geodesy (GEO) formulation was used to convert the geodesy coordinate to Euclidean or polar coordinate. The Haversine equation obtained the distance between the two points.
 The system performance and stability of the tracking controller are proved using the Lyapunov theorem of the stability. A python script was used in this work as a simulator. Computer simulation with pose to pose trajectory strategy conform to the simplicity of the proposed controller.
Highlights
The goal is to develop a kinematic controller of an autonomous mobile robot that can navigate from converting the geodesy coordinate to the polar coordinate system by haversine formulation
In this paper, a modified stabilized kinematic controller for point to point in the polar coordinate system was proposed
It was applied in tracking control of non-holonomic wheeled mobile robot (WMR)
Summary
The goal is to develop a kinematic controller of an autonomous mobile robot that can navigate from converting the geodesy coordinate to the polar coordinate system by haversine formulation. The dead reckoning includes some source of errors as white noise and accumulative errors Another way for indoor navigation uses a camera (Cunha et al 2011). (Muñoz, Muñoz-Panduro, and Ramos 2018) work proposed a collision-free trajectory using Artificial Potential Fields and sensed depth data from the surrounding environment They used a closed loop controller based on polar coordinates, which is led by a potential field. Control systems that have been proposed for various differential WMR ( Wheeled Mobile Robot ) can be divided into two classes, a dynamic controller (Martins and Brandão 2018; Al-Araji and Ibraheem 2019) and kinematic controller (Lee et al 2000). This work modified a polar kinematic controller that compensates the velocity before reach the limited value
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