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Single Sensor Navigation for Unmanned Indoor Ground Vehicles Using Fuzzy Rules


Authors : Peter Ndajah; Ishaya Emmanuel

Volume/Issue : Volume 11 - 2026, Issue 4 - April


Google Scholar : https://tinyurl.com/2u5fw52c

Scribd : https://tinyurl.com/bdsr7a3h

DOI : https://doi.org/10.38124/ijisrt/26apr115

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : Obstacle detection and avoidance systems as a research area have been gaining attention lately, but the issues of blind areas and ground/small obstacle problems have received little interest, especially indoor autonomous navigation. In this work, we present an environment-sweep technique for obstacle detection and a fuzzy algorithm for ground obstacle avoidance, surface elevation estimation, and obstacle classification for indoor robots that eliminates the blind area problem. We employed an ultrasonic sensor on a servo for environmental sweep to eliminate blind areas. Results show that the issue of interference was mitigated by the servo sweep technique we propose. Fuzzy algorithms combined with a single ultrasonic sensor reduced the complexity of the robot, thereby improving the robot's performance in real-time. Fuzzy algorithms combined with a differential wheel driving mechanism speed up the inference and actuation process of the proposed system. This is due to fewer rules and a less complex yet effective algorithm design that converts steering angles to different wheel speeds, making the response time much less than the stipulated threshold of 2s as has been determined in previous literature.

Keywords : Self-Adaptation, Linear Regression, Environmental Variant, Design Pattern, Reusability, Software Variant, Load Balancer.

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Obstacle detection and avoidance systems as a research area have been gaining attention lately, but the issues of blind areas and ground/small obstacle problems have received little interest, especially indoor autonomous navigation. In this work, we present an environment-sweep technique for obstacle detection and a fuzzy algorithm for ground obstacle avoidance, surface elevation estimation, and obstacle classification for indoor robots that eliminates the blind area problem. We employed an ultrasonic sensor on a servo for environmental sweep to eliminate blind areas. Results show that the issue of interference was mitigated by the servo sweep technique we propose. Fuzzy algorithms combined with a single ultrasonic sensor reduced the complexity of the robot, thereby improving the robot's performance in real-time. Fuzzy algorithms combined with a differential wheel driving mechanism speed up the inference and actuation process of the proposed system. This is due to fewer rules and a less complex yet effective algorithm design that converts steering angles to different wheel speeds, making the response time much less than the stipulated threshold of 2s as has been determined in previous literature.

Keywords : Self-Adaptation, Linear Regression, Environmental Variant, Design Pattern, Reusability, Software Variant, Load Balancer.

Paper Submission Last Date
30 - April - 2026

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