Multi-Axis Robot Arm with Mobile Control and Real-Time Object Recognition

This paper implemented an advanced robotic arm managed through a mobile application on an Android device employing Bluetooth technology to link the smartphone with an Arduino board for the seamless and distant operation of the arm. The Android application features sliders for manual adjustment of servo positions and buttons for storing, executing, and resetting preprogrammed motions, allowing users to independently manage each arm joint or perform a series of actions automatically. The proposed mechanical arm has five degrees of freedom for joints, a gripping mechanism, and a platform with Mecanum wheels for movement in all directions, which helps in maneuverability in confined areas. A camera module from ESP is also integrated into the setup to detect and recognize objects in time through OpenCV for image processing and the YOLO algorithm for object identification. Due to the integration of Bluetooth control technology, computer vision, and enhanced mobility features in the system design, the robotic arm is more accurate, flexible, vulnerable, and cheaper than the existing solutions.

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Publication Details

Published
2025-06-05
DOI
https://doi.org/10.1109/eaic66483.2025.11101345
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
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Multi-Axis Robot Arm with Mobile Control and Real-Time Object Recognition

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Robotics and Sensor-Based Localization
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Multi-Axis Robot Arm with Mobile Control and Real-Time Object Recognition

Nitin Kumar Chauhan, A. M. Awasthi, Ankit Jain, Anuj Dhakariya, Sonali Singh Rajawat, Harshita Patidar
article en

Abstract

This paper implemented an advanced robotic arm managed through a mobile application on an Android device employing Bluetooth technology to link the smartphone with an Arduino board for the seamless and distant operation of the arm. The Android application features sliders for manual adjustment of servo positions and buttons for storing, executing, and resetting preprogrammed motions, allowing users to independently manage each arm joint or perform a series of actions automatically. The proposed mechanical arm has five degrees of freedom for joints, a gripping mechanism, and a platform with Mecanum wheels for movement in all directions, which helps in maneuverability in confined areas. A camera module from ESP is also integrated into the setup to detect and recognize objects in time through OpenCV for image processing and the YOLO algorithm for object identification. Due to the integration of Bluetooth control technology, computer vision, and enhanced mobility features in the system design, the robotic arm is more accurate, flexible, vulnerable, and cheaper than the existing solutions.

Indian Institute of Technology Indore (IN)
Openalex Percentile: Top 71%
Robotics and Sensor-Based Localization
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