Evaluation of Classifier Architectures and Ultrasound Features for Robotic Wall-Following Navigation
DOI:
https://doi.org/10.48047/p6jqbh44Keywords:
Keywords: Autonomous navigation, wall following robots, Ultrasound sensor features, Supervised learning, KNN classifier, DTC model.Abstract
Wall-following navigation is an essential capability for autonomous robots in structured environments such as warehouses, factories, and homes. This research enhances both the accuracy and reliability of wall-following by evaluating and optimizing machine learning classifiers built on ultrasound sensor features. Traditional approaches—rule-based algorithms coupled with basic ultrasonic sensors and fixed thresholds—often lack the precision, adaptability, and real-time performance required for effective navigation in dynamic settings
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