Development of a Mecanum-Wheeled Mobile Robot for Dynamic- and Static-Obstacle Avoidance Based on Laser Range Sensor

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Abstract

This study aims to present an idea about the practical consequences of using mobile robots with Mecanum wheels. For mobile robots, an approach is proposed to avoid obstacles without location and map information. This approach is presented using a series of developed solutions. This article shares the process on how a set of discussed conceptual methodologies can be applied as well as their practical results. This method is provided using fuzzy logic and gap tracking. LIDAR is used to recognize obstacles around the mobile robot. By using the LIDAR, the robot detects gaps around it and moves according to fuzzy logic. The fuzzy logic consists of three inputs, an output, and 45 rules. The first of the membership functions represents the membership function that replaces the obstacle. The second membership function calculates the distance to the obstacle. The final login membership function is used to determine the angle between the obstacle and robot view. The output membership function represents the membership function that moves the robot. The results are analyzed under three different scenarios with five different experiments for each scenario. The results show that the mobile robot can avoid obstacles without location and map information. We believe that the proposed method can be used in mobile robots such as guard and service robots.

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APA

Matli, M., Albayrak, A., & Bayir, R. (2020). Development of a Mecanum-Wheeled Mobile Robot for Dynamic- and Static-Obstacle Avoidance Based on Laser Range Sensor. International Journal of Fuzzy Logic and Intelligent Systems, 20(3), 188–200. https://doi.org/10.5391/IJFIS.2020.20.3.188

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