Very Short Summary
A 5-DOF robotic arm that mimics human arm motion in real-time using MPU6050 sensors, Arduino Uno, and CoppeliaSim simulation.

Aim
To develop a robotic arm capable of accurately replicating human arm movements in real-time using motion sensors and simulate its behavior in CoppeliaSim.

Introduction
This project aims to design and implement a robotic arm that can mirror the motion of a human arm with high accuracy. The system integrates mechanical, electronic, and software components to enable real-time motion tracking and replication. Motion data is captured using an MPU6050 sensor and processed via Arduino Uno before being transmitted to a simulation in CoppeliaSim.

Literature Survey and Technologies Used
MPU6050: A 6-axis sensor combining gyroscope and accelerometer for tracking orientation.

Arduino Uno: A microcontroller used for reading sensor data and transmitting it for processing.

CoppeliaSim: A robotic simulation platform used to visualize and test the robotic arm model.

SolidWorks: Used for CAD modeling of the robotic arm.

I2C Communication: Enables sensor-Arduino data transfer with just two wires (SDA, SCL).

Existing research highlights motion replication for applications in rehabilitation and teleoperation.

Methodology
Mechanical Design:

• CAD model created in SolidWorks with 5 Degrees of Freedom:
  • Shoulder: 2 DOF (spherical)
  • Elbow: 1 DOF (revolute)
  • Wrist: 2 DOF (spherical)
• Sensor Integration:
  • MPU6050 mounted on user's arm to track pitch, roll, and yaw.
• Arduino Data Processing:
  • Sensor data filtered using complementary filtering techniques.
  • Converted to angle values suitable for robotic arm control.
• Communication:
  • Processed data sent via serial communication (USB) to PC.
• Simulation:
  • CoppeliaSim receives data and updates robotic joint angles accordingly via remote API.

Results
The virtual robotic arm in CoppeliaSim accurately mirrored real-time human arm movements.

Sensor data was consistently processed with low latency, ensuring smooth and responsive control.

Realistic joint behavior was observed for the shoulder, elbow, and wrist.

Conclusion & Future Scope
Conclusion:

Successfully achieved real-time replication of human joint motion in simulation.

Demonstrated stable sensor integration and control system.

Future Scope:

Implement multiple IMUs for full arm tracking with increased precision.

Develop a physical hardware prototype based on the simulation model.

Apply system for assistive technologies, VR/AR control, or remote robotic operations.

References / GitHub Links
GitHub Repository (https://github.com/IEEE-NITK/I05-Robotic-Arm)

MPU6050 Datasheet

Arduino Documentation

CoppeliaSim Documentation

Mentor & Mentee Details
Mentors:

Pranav Sudheer

Shankaragouda

Mentees:

Santo Davis