Omni-Bot Pick and Place Robotic Arm: A Review

Abstract

This project describes the design and implementation of a mobile robotic arm controlled through a wireless Bluetooth system. In this setup, an HC-05 Bluetooth module is connected to the Raspberry Pi to create communication between an Android mobile application and the robotic unit. The communication is carried out using UART serial protocol, which allows reliable transmission of control commands. The robotic arm is built with four degrees of freedom (4-DOF), enabling flexible movement such as base rotation, arm lifting, gripping, and object placement. The arm can rotate up to 270 degrees to cover a wider working area. Servo motors are used to achieve accurate positioning and smooth motion control. In addition to the arm mechanism, wheels are attached to the base so that the system can move from one location to another. In many small-scale industries, warehouses, and manufacturing units, pick-and-place work is still done manually. Workers have to lift, move, and place objects continuously, which increases physical effort and causes tiredness. In some cases, it can be unsafe, especially when the materials are heavy or hazardous .Most industrial robotic systems available in the market are costly and cannot be easily afforded by small industries or educational institutions. The proposed system aims to reduce human effort, improve productivity, and provide a practical automation solution at an affordable cost.

Introduction

The paper describes the development of a robotic arm system designed to reduce human labor and improve efficiency in industrial and automation applications. Robotics is rapidly advancing and is widely used in industries, medicine, and education for performing repetitive and complex tasks with high accuracy. The proposed system uses a Raspberry Pi as the main control unit to manage movement and operations, making the system flexible and efficient.

The robotic arm integrates mechanical structure, electronic components, and software control. It includes features such as object detection, line following, and pick-and-place operations. Key components of the system include sensors (IR and ultrasonic), servo motors (MG90S), DC motors, a motor driver (L293D), power supply, joystick control, and a gripper. The motor driver enables safe control of motors, while the gripper performs object handling tasks. The system can rotate up to 270 degrees and is suitable for automation tasks in industries to improve productivity, accuracy, and speed.

The literature review highlights similar robotic arm systems developed using Raspberry Pi, cameras, IoT, deep learning, and microcontrollers, focusing on applications such as industrial automation, color sorting, hazardous object handling, and flexible manufacturing. Many systems aim to reduce costs, improve efficiency, and enable remote or intelligent control.

The proposed methodology combines manual joystick control and sensor-based automation, allowing flexible operation. The IR sensor supports object detection and line-following tasks, while the Raspberry Pi processes input signals to control motor movement.

Future improvements include:

• ???? Integrating a camera with object detection for better automation

• ???? Adding voice control for hands-free operation

• ???? Implementing automatic charging for continuous operation

Overall, the system demonstrates a low-cost, efficient, and adaptable robotic arm solution for industrial and automation purposes, with potential for further enhancement through smart technologies.

Conclusion

In this project, a robotic arm system was developed to perform pick-and-place operations automatically. The system uses a Raspberry Pi, camera module, and servo motors to detect and move objects from one position to another. Image processing techniques help in identifying the object correctly, and the robotic arm performs the task without manual support. The system works properly for small-scale industrial applications and reduces human effort. This project shows how automation and image processing can be combined to improve accuracy and efficiency in practical applications.

References

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Copyright

Copyright © 2026 Swapnaja Yande, Vidya Pradhan, Vaishnavi Sapkal, Pooja Paygavhan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.