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Authors
Kurapati Sasi Srija,Sidagam Anirudh,Sadhanala Himasri,P.V.S Harsha Vardhan,Vemula Bhaskar Ajay
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Keywords
Keywords: Hand Gesture Recognition, 6-DOF Robotic Arm, Human-Robot Interaction (HRI), MediaPipe Hands, Computer Vision, Machine Learning, K-Means Clustering, Smart Presets, Exponential Moving Average (EMA), Deadband Filtering, Arduino UNO, PCA9685 Servo Driver, Real-Time Control System, Flask Web Application, Three.js Visualization.
Abstract
Apprentice Arm is a 6-Degree-of-Freedom, hand-gesture
controlled, real-time. (6-DOF) robotic arm system based on the use
of computer vision, machine learning, and embedded systems to
allow contactless, intuitive robotic manipulation. The system will
live video on a regular USB webcam, and will extract 21 three
sided video. dimensional hand landmarks with MediaPipe Hands
deep-learning of Google. pipeline, and maps the spatial geometry
of the hand of the user into six. independent servo motor angles
Base rotation,Shoulder lift, Elbow bend, Wrist Pitch, Wrist Roll
and Gripper open/close-in real time. The software layer is
developed using a Python Flask back-end which integrates. Hand
tracking using MediaPipe, Exponential Moving Average (EMA)
signal. deadband filtering, smoothing and serial communication
into one. cohesive application. The backend is annotated MJPEG
video which is being streamed to a modern. web dashboard
(HTML5/CSS3/JavaScript) that features a live camera feed, an
interactive Three.js 3D digital twin of the robotic arm, six manual
override. sliders, a complete task recorder and player engine and
an ML-based Smart. Presets module which opts K-Means
clustering (scikit-learn) to automatically. find and propose the
most common arm positions based on recorded. task history.
Hardware On the hardware side, an Arduino UNO
microcontroller receives commands regarding the angles. over a
9600-baud UART serial connection and drives a 16 channel I2C
PWM, the PCA9685. servo driver. The Base, Shoulder, and have
three MG996R high-torque servos. Elbow joints: There are three
SG90 micro-servos that drive the Wrist Pitch, Wrist. Roll, and
Gripper. The servos use two 3.7 V lithium-ion as a power source.
batteries (in series) (~7.4 V), reduced to a regulated (~5.5 V). with
an LM2695 DC-to-DC buck converter and then to the V+ of
PCA9685. servo power rail. The Apprentice Arm has a gesture to
servo end-to-end latency of. around 60 ms, a hand-tracking
frequency of 30 FPS, a refresh of the dashboard. frequency of 12.5
Hz, and 3D frame rate of over 60 FPS. The system is developed to
be modular, reproducible and extensible, which is why it is
suitable. in the case of academic research, educational
demonstrations, and hobbyist robotics. HRI projects.
IJCRT's Publication Details
Unique Identification Number - IJCRT2604754
Paper ID - 306188
Author type - Indian Author
Page Number(s) - g475-g483
Pubished in - Volume 14 | Issue 4 | April 2026
DOI (Digital Object Identifier) -
No Of Downloads - 73
Author Country - India, 521137, Vijayawada, Vijayawada, 521137, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT2604754
Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRT2604754
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Kurapati Sasi Srija,Sidagam Anirudh,Sadhanala Himasri,P.V.S Harsha Vardhan,Vemula Bhaskar Ajay, "Apprentice Arm", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.14, Issue 4, pp.g475-g483, April 2026, Available at :http://www.ijcrt.org/papers/IJCRT2604754.pdf
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