Motion Sense Rover Using Arduino Nano

Abstract

This project presents a hand gesture–controlled car system designed to improve human–machine interaction using simple and cost-effective technology. This project presents a hand gesture–controlled car system designed to improve s instead of traditional remote controls. The system uses an accelerometer sensor mounted on a hand glove to detect hand gestures such as forward, backward, left, and right movements. These gestures are transmitted wirelessly using an RF transmitter and receiver module. An Arduino Nano micro -controller is used to process the received signals and control the motors of the car through a motor driver module. The system is programmed using Embedded C in the Arduino IDE.

Introduction

The project presents a Hand Gesture Control Car, a robotics system that allows users to control a car using hand gestures instead of traditional remote controllers. It aims to create a more natural, wireless, and user-friendly human-machine interaction, especially beneficial for physically disabled individuals or situations where remotes are inconvenient.

The system uses an MPU6050 sensor (accelerometer and gyroscope) to detect hand movements, which are processed by an Arduino Nano. The processed signals are transmitted wirelessly (via RF/Bluetooth) to another Arduino on the car, which controls the motors through a motor driver.

The methodology involves:

• Collecting gesture data (e.g., forward, backward, left, right, stop),
• Preprocessing inputs using smoothing and dead zones to avoid noise,
• Extracting features like pitch and roll angles,
• Using lightweight models such as threshold-based logic, KNN, or TinyML for gesture recognition.

The system is trained by setting angle thresholds (e.g., 20° tilt) and mapping gestures to motor speed. Testing involves evaluating how accurately gestures control the car.

Results show strong performance, with an average accuracy of around 95%, and highest accuracy for the “stop” gesture (97%). The system demonstrates reliable gesture recognition and effective wireless control.

Overall, the project provides a low-cost, efficient, and intuitive solution for gesture-based vehicle control, with potential for further improvement using advanced AI techniques.

Conclusion

This project presents the design and implementation of a hand gesture-controlled car using the Arduino Nano and the MPU6050 Sensor. The system successfully translates human hand movements into control commands for vehicle navigation, enabling a natural and intuitive human–machine interaction. The use of an accelerometer and gyroscope-based sensor allows accurate detection of gestures such as forward, backward, left, right, and stop. These gestures are transmitted wirelessly through the RF Transmitter and Receiver Module and executed using the L298N Motor Driver Module. The system achieved an overall accuracy of object for various applications such as robotics and assistive technologies. However, certain limitations such as gesture misclassification, signal interference, and limited processing capability were observed.

References

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Copyright

Copyright © 2026 Snehal Govardhan, Sourabh Singh, Duneshwar Patel, Rounak Singh Thakur, Rohan Kumar Rathore. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.