International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 09 | Sep 2025
p-ISSN: 2395-0072
www.irjet.net
Hand gesture motion controlled pick and place object robotic vehicle Abdul Hadi Akhlaque Khatib1, Siddharth Sanjay Salvi2, Karan Raju Barde3, Aniket Chandrakant Shigvan4 1Abdul Hadi Akhlaque Khatib, Mangaon, Raigad, 402103. 2Siddharth Sanjay Salvi, Mangaon, Raigad, 410205. 3Karan Raju Barde Roha, Raigad,402109 ,
4Aniket Chandrakant Shigvan Mangaon, Raigad, 402104. Dept. of electrical Engineering, DBATU, lonere, Raigad, Maharashtra, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The development of intuitive human-robot
The proposed system addresses several limitations of conventional robotic control methods including physical strain during prolonged operation, limited accessibility for differently-abled users, safety concerns in hazardous environments, and complex learning requirements for traditional interfaces. The development of this gesturecontrolled robotic vehicle aims to provide an intuitive, wireless, and efficient solution for pick and place operations in industrial and domestic environments.
interaction systems has become crucial in modern robotics applications. This paper presents the design and implementation of a hand gesture motion-controlled robotic vehicle capable of pick and place operations using accelerometer sensors and RF communication. The system consists of two main units: a transmitter unit equipped with ADXL335 accelerometer and Arduino Nano for gesture detection, and a receiver unit with Arduino Uno controlling DC gear motors through L298N motor drivers. The proposed system eliminates the need for traditional button-based controllers, providing a more natural and accessible interface for robotic control. Experimental results demonstrate successful operation with 200-300ms response time, 44 meters operational range, and 1100 grams payload capacity. The system achieves 96-98% gesture recognition accuracy with 2-hour battery life, making it suitable for industrial automation, medical assistance, and hazardous environment applications.
1.1 Problem Statement Current robotic control systems face significant challenges in terms of user accessibility and operational efficiency. Wired button-controlled robots become bulky and limit operational distance, while wireless controllers still require physical button presses that can cause finger strain during extended use. Additionally, these systems are not suitable for users with physical disabilities and pose safety risks in hazardous environments where direct operator presence is dangerous.
Key Words: Hand gesture recognition, Robotic vehicle, Pick and place, Accelerometer, RF communication, Arduino, Human-robot interaction, ADXL335.
1.2 Objectives The primary objectives of this research include: measuring hand gestures using accelerometer sensors, identifying movement directions through signal processing, encoding gesture data for RF transmission, receiving and decoding control signals, and implementing precise robot movement control based on decoded commands. The system aims to achieve reliable wireless communication, intuitive gesture recognition, and efficient pick and place operations.
1. INTRODUCTION The evolution of robotics technology has consistently focused on improving human-machine interaction interfaces. Traditional robotic control systems rely heavily on complex joystick controllers and button-based interfaces, which can be challenging for users with disabilities and create operational barriers in time-critical applications. Hand gesture recognition has emerged as a natural and intuitive alternative, allowing operators to control robotic systems through simple hand movements without physical contact with control devices. Recent advances in microelectromechanical systems (MEMS) technology and wireless communication protocols have made gesture-based control systems more accessible and cost-effective. The integration of accelerometer sensors with microcontroller platforms provides a practical solution for developing responsive gesture recognition systems that can be implemented in various robotics applications.
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Impact Factor value: 8.315
2. LITERATURE REVIEW Anderez et al. (2019) demonstrated accelerometer-based hand gesture recognition for human-robot interaction, achieving 95.85% accuracy using a wrist-mounted tri-axial accelerometer with adaptive segmentation techniques. Their research established the foundation for reliable gesture recognition in robotics applications using computational solutions with gesture sets including directional movements. Neto et al. (2019) proposed a gesture-based HRI framework using inertial measurement units (IMUs) for manufacturing assistance applications. Their system implemented artificial
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