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This paper proposes an autonomous robot for real-time pothole detection and refilling, enhancing road infrastructure maintenance. The system integrates Machine Learning (ML) and OpenCV for accurate pothole identification and uses ultrasonic sensors for detecting surface irregularities. A camera mounted on the robot captures visual data, while ultrasonic sensors provide real-time feedback. Managed by an Arduino microcontroller, the robot autonomously navigates roads, halting to deploy filler material via DC motors from an onboard container. Zigbee modules enable wireless data transmission for monitoring and coordination. This solution improves road safety, minimizes human intervention, and offers a scalable, cost-effective approach to road maintenance.

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Real-Time Pothole Detection and Automated Refilling Robot Using ML and OpenCV

  • 会议论文

  • 发表日期：

    2026年

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  • D. Kalaivani,
  • N. B. Madhura,
  • Mahima Ramdas Bhat,
  • A. Gowthami,
  • Raksha Shankar Kajagar

摘要

This paper proposes an autonomous robot for real-time pothole detection and refilling, enhancing road infrastructure maintenance. The system integrates Machine Learning (ML) and OpenCV for accurate pothole identification and uses ultrasonic sensors for detecting surface irregularities. A camera mounted on the robot captures visual data, while ultrasonic sensors provide real-time feedback. Managed by an Arduino microcontroller, the robot autonomously navigates roads, halting to deploy filler material via DC motors from an onboard container. Zigbee modules enable wireless data transmission for monitoring and coordination. This solution improves road safety, minimizes human intervention, and offers a scalable, cost-effective approach to road maintenance.