Smart Navigation Voice Controlled Vehicle

Abstract

A Voice-Controlled vehicle with Object recognition project integrates technologies like speech recognition and computer vision to create an intelligent vehicle that can be controlled through voice commands and can also identify objects in its environment. In defence applications, this system aims to enhance surveillance, reconnaissance, and situational awareness, reduce human risk in hazardous zones, and provide efficient, real-time decision-making support through automated detection and interaction with potential threats. Our project approach will be by means of implementing an Arduino microcontroller into the vehicle chassis and programming it such that the DC motors should be controlled by voice commands and integrating an ultrasonic sensor and a camera with the vehicle to detect objects. The result will be an autonomous vehicle that can be controlled by voice commands and provide thepictures of the detected objects on the connected Android device.

Introduction

The text describes the development of a Smart Navigation Voice-Controlled Vehicle, which uses modern technologies like embedded systems, AI, and IoT to improve vehicle safety, convenience, and user interaction through voice commands.

The system is built as a prototype using components such as an Arduino Uno, voice recognition module, L298N motor driver, ultrasonic sensors, ESP32-CAM, and Bluetooth communication, all integrated on a chassis powered by a 12V battery. The vehicle can interpret voice commands like moving forward, turning, and stopping, while also performing automatic obstacle detection and avoidance using ultrasonic sensors.

Testing shows that the system performs reliably in controlled conditions, with:

• 95% voice command accuracy
• 98% obstacle detection accuracy
• ~200 ms response time
• ~90 minutes battery life
• Bluetooth range close to 9.5 meters

Conclusion

The Smart Navigation Voice-Controlled Vehicle project successfully designed and developed a mobile robotic system controlled via voice commands with intelligent obstacle avoidance capabilities. The system integrates voice recognition through a smartphone, Bluetooth communication for wireless control, and an Arduino-based microcontroller. The project involved hardware assembly, circuit design, software development, and real-time testing. Testing confirmed the accuracy, responsiveness, and reliability of the vehicle under normal conditions, demonstrating its potential applications in assistive technology, education, and service robotics.

References

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Copyright

Copyright © 2026 Dr. B. Ramakrishna, Dr. D. Kameswara Rao, Dr. K. Sudhakar Reddy, M. Tharun. 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.