Smart Terrain-Aware Navigation: An Embedded Robotic System for Obstacle Avoidance and Surface Detection

Abstract: This paper presents the creation of an economical, self-sufficient mobile robot intended for real-time obstacle avoidance and detection of uneven surfaces, ensuring safe and efficient navigation in unstructured settings. Constructed on the Arduino Uno platform, the system incorporates an HC-SR04 ultrasonic sensor for proximity-based obstacle detection and an MPU6050 accelerometer/gyroscope module to identify surface inclinations and irregular terrains. Additionally, the robot features an L298N motor driver that facilitates precise movement control, while a 16×2 LCD module offers ongoing feedback regarding system status and environmental conditions. The approach includes sensor fusion, modular hardware integration, and embedded software design, enabling robust decision-making and real-time adaptability. Experimental assessments reveal the system’s capability to navigate various terrains and avoid obstacles with minimal latency and high precision. The design's modularity, cost-effectiveness, and ease of deployment render it suitable for numerous applications, such as industrial automation, educational robotics, exploration, and disaster response. The findings highlight the potential of integrating obstacle avoidance with surface detection within a cohesive framework to improve autonomous robotic mobility in intricate real-world situations.

Autonomous Navigation, Obstacle Avoidance, Uneven Surface Detection, Arduino Uno, Ultrasonic Sensor, MPU6050 Accelerometer.

1. Arduino Documentation, "Arduino Uno Technical Specifications," https://www.arduino.cc. [Google Scholar] [Crossref]

2. HC-SR04 Ultrasonic Sensor Datasheet. [Google Scholar] [Crossref]

3. MPU6050 Accelerometer/Gyroscope Datasheet. [Google Scholar] [Crossref]

4. L298N Motor Driver Module Guide. [Google Scholar] [Crossref]

5. Bharti, A. K., Bharati, A. K., Raza, A., Kumar, A., & Aamir, A. (2022). Obstacle avoiding robot: A review. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 10(5), 1234–1240. https://doi.org/10.22214/ijraset.2022.43056 [Google Scholar] [Crossref]

6. Molina, M., Vera, A., Molina, C., & Garzon, P. (2018). Design and construct an obstacle-avoiding robot using the Arduino platform and programming tools. In 2018, 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) (pp. 788–791). IEEE. https://doi.org/10.1109/UEMCON.2018.8796577 [Google Scholar] [Crossref]

7. Patel, M., Sharma, S., & Gupta, D. (2020). Design and control of terrain adaptive mobile robots: A review. Robotics and Autonomous Systems, 131, 103579. https://doi.org/10.1016/j.robot.2020.103579 [Google Scholar] [Crossref]

8. Sarkar, A., Kumar, V., & Bandyopadhyay, S. (2020). Low-cost ultrasonic sensor applications for robotics. Journal of Instrumentation and Control Engineering, 8(3), 12–19. [Google Scholar] [Crossref]

9. Yin, T., Zhang, H., & Lee, D. (2021). Sensor fusion in autonomous navigation systems: Challenges and future trends. Sensors, 21(2), 456. https://doi.org/10.3390/s21020456 [Google Scholar] [Crossref]

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