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@article{198469,
        author = {KRISHNAN B and Dhinesh G and Ashok R and Padmapriya K and Gayathri M and Kaleeswaran K},
        title = {INTELLIGENT ROBOTIC ARM SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {10385-10392},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198469},
        abstract = {Human–robot interaction has become a key research area in robotics and automation. This paper presents a real-time hand gesture–controlled robotic arm system using computer vision techniques. A webcam captures hand gestures, which are processed using OpenCV and MediaPipe in Python to detect hand landmarks and finger movements. Recognized gestures are mapped to corresponding robotic arm actions such as directional movement and gripper control. The gesture commands are transmitted via serial communication to a NodeMCU (ESP8266) microcontroller, which controls DC motors through an L298N motor driver. The proposed system provides an intuitive, contactless, and low-cost solution for robotic arm control. Experimental results demonstrate accurate gesture recognition and reliable robotic arm response in real time, making the system suitable for industrial automation, assistive robotics, and remote handling applications.},
        keywords = {Hand gesture recognition, robotic arm, computer vision, OpenCV, MediaPipe, NodeMCU, human–machine interaction.},
        month = {April},
        }