Assessfy Pvt. Ltd Advanced 5 milestones 100 marks

Robotic Arm with Computer Vision for Pick-and-Place Automation

Target year: BE Sem 7-8 (Major Project Phase-I/II) AICTE: 6 credits · ~150 hrs Bloom: Create / Evaluate MU CBCS: MEC801 / MEDLO8021 BE Project

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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Milestones

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Core skills

About this project

Build a 4-DOF robotic arm that uses a USB camera + computer vision to detect, classify, and pick coloured objects from a conveyor and sort them into bins. Combines mechanical design, embedded control, and applied CV. Aimed at warehouse / FMCG sorting automation.

Course Learning Outcomes (CLOs):
CLO1: Apply forward + inverse kinematics to a multi-DOF arm.
CLO2: Implement camera-based object detection + classification using OpenCV.
CLO3: Calibrate camera coordinates to robot-arm workspace.
CLO4: Integrate mechanical, embedded, and software layers into a working system.
CLO5: Evaluate system performance: pick success rate, cycle time, repeatability.

Industry/societal relevance: Direct preparation for warehouse-automation roles at Flipkart Robotics, GreyOrange, Addverb, Amazon Robotics India.

Milestones

1. Mechanical Design + 3D Print

15 marks 18d

CAD the arm in Fusion 360, print PLA parts, assemble with servos. Verify each joint reaches expected angles.

2. Kinematics + Servo Control

20 marks 21d

Implement FK + IK in Python on Raspberry Pi. Demo: command (x, y, z) → arm moves to that position within ±5mm.

3. Vision Pipeline

25 marks 21d

OpenCV pipeline: capture frame, segment by HSV color, find centroid + bounding box of each object. Test on 3 colours.

4. Camera-to-Arm Calibration

20 marks 18d

Place 9 fiducial markers, solve perspective transform from image coords to arm-workspace coords. Validate accuracy.

5. Full Demo + Performance Report

20 marks 22d

End-to-end: object on conveyor → vision detects → arm picks → drops in correct bin. Measure success rate over 50 trials, cycle time, repeatability. 12-page report + oral defense.

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Skills you'll learn

Robot kinematics (forward + inverse)Servo controlComputer Vision (OpenCV)PythonArduino/Raspberry Pi3D printingCoordinate calibration (camera-to-arm)

Tools used

Raspberry Pi 4USB webcam4× MG996R servosArduino UNOPython 3.11OpenCV 43D printer (PLA)GitHub

Prerequisites

Robotics; Manufacturing Processes; basic Python; comfort with Linux command line

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