AI-Driven Gesture Recognition for Robotic Control

Authors

  • D. N. V. S. Vijaya Lakshmi, Prasad Rayi, V. Rambabu, Ch S K Chaitanya

Keywords:

Gesture Recognition, Image Processing, Opencv, Human-Computer Interaction (HIC), Python, Machine Learning, Wireless Communication.

Abstract

In our planet, several individuals use gestures, a really effective communication tool among people. Actions are more instinctive than verbal expressions. Gestural communication is an effective modality. Wireless communication systems are extensively used and implemented in many industrial settings and residential areas. In our gesture control project, a two-wheeled robot is operated by diverse hand gestures. Gesture recognition employs several image processing techniques to identify picture signals. Robots may assume many forms, but some replicate the look of living organisms. These robots engage with people directly, making the interface user-friendly. The first gadgets were primarily used for navigation and robotic control without any organic interface. To address this demand, we have initiated a project that involves sending orders to the robot using hand gestures. This image processing technique enables us to manipulate the robot with our fingertips. We used image processing techniques to collect these directives. Consequently, the robot need to navigate in the specified direction.

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References

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Published

05.05.2025

How to Cite

D. N. V. S. Vijaya Lakshmi. (2025). AI-Driven Gesture Recognition for Robotic Control. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 1060–1065. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7492

Issue

Vol. 11 No. 4 (2023)

Section

Research Article

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