Authors:
O. Jeba Singh, E. Anna Devi, S. Rubin Bose, J. Angelin Jeba, Andino Maseleno, S. Nimmi Devi
Addresses:
Centre for Academic Research, Alliance University, Bengaluru, Karnataka, India. Department of Electronics and Communication Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. School of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamil Nadu, India. Department of Electronics and Communication Engineering, S.A. Engineering College, Chennai, Tamil Nadu, India. Department of Information Systems, Institut Bakti Nusantara, Pringsewu, Lampung, Indonesia. Department of Artificial Intelligence and Data Science, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India.
Abstract:
This study reports the creation of a robotic arm that uses hand gestures in real time and is controlled by computer vision and the Zigbee wireless network. The main aim is to develop a user-friendly human-machine interface that enables the selection of robotic hardware using natural hand movements, without physical controllers or tethering. The system uses a standard high-definition webcam to capture visual data, which is then processed with the MediaPipe framework and the OpenCV library to detect hand landmarks and gestures accurately. The investigation involves a purpose-built dataset of hand gestures comprising 422 cases, grouped into definite commands: Grip, release, rotate, and directional movement. Zigbee modules enable wireless data transmission by consuming low power and supporting point-to-point communication. This is a real-time image-processing method that maps hand coordinates to the robotic arm's joint angles. The findings show that the accuracy level and the minimum latency of command execution were high. The system exhibits high performance across different lighting conditions and user hand shapes. This integration of optical sensing and wireless telemetry offers an expandable architecture for industrial control, medical assistance, and the discovery of remote, hazardous environments, where precision remote manipulation is necessary.
Keywords: Computer Vision; Robotic Arm; Zigbee Communication; Hand Gesture Recognition; Human-Machine Interaction; Optical Sensing; OpenCV Library; MediaPipe Framework; Intelligent Systems.
Received on: 23/06/2025, Revised on: 14/08/2025, Accepted on: 09/09/2025, Published on: 05/03/2026
DOI: 10.64091/ATICR.2026.000306
AVE Trends in Intelligent Computing Research, 2026 Vol. 1 No. 1 , Pages: 1-11