Improving AI Text Recognition Accuracy with Enhanced OCR For Automated Guided Vehicle

  • Florentinus Budi Setiawan Universitas Katolik Soegijapranata Semarang
  • Farrel Adriantama Universitas Katolik Soegijapranata Semarang
  • Leonardus Heru Pratomo Universitas Katolik Soegijapranata Semarang
  • Slamet Riyadi Universitas Katolik Soegijapranata Semarang
Keywords: OCR, AGV, Image Processing, Computer Vision, AI


This artificial intelligence robot uses a mini-computer to operate it and uses mechanical movement like a four-wheeled vehicle with a 2WD drive system. In this article, a control strategy of the AGV robot will be shown and implemented to detect the location. This research Uses OCR (Optical Character Recognition) for the OpenCV library itself which has been enhanced/modified. This enhanced OCR is the main library used in text recognition. This research produces very accurate text detection compared to the default OCR that was previously used on the AGV robot in our university. After the process of reading this text is passed, it will produce text previously read through the camera which will then provide output in the form of text where the AGV robot is located. After the reading is validated, the AGV robot will move to the next point until it returns to its starting point. Based on hardware implementation through testing in the AGV laboratory with artificial intelligence, it can work according to the algorithm and minimize reading errors with a 95% success rate.


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How to Cite
Florentinus Budi Setiawan, Adriantama, F., Leonardus Heru Pratomo, & Slamet Riyadi. (2022). Improving AI Text Recognition Accuracy with Enhanced OCR For Automated Guided Vehicle . Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 6(5), 728 - 734.
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