Delta Robot

MCT 211

Faculty Of Engineering & Technology

ECU

Members

1.JASON GEORGE 192300357 2.JONATHAN RAMY 192300333

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3.MAHRAIL FAISAL 122400012 4.MARIAM EZZ 192300605

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5.MARIAM KAMAL 192300328 6.MARIAM MOSTAFA 192300611

7.MARIO JOHN 192300330 8.MARVINA EMAD 192300285

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9.MARWAN HISHAM 192300402 10.MAYAR ELHADI 192300614

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11.SALMA MOHAMED 192300327 12.YOUSSEF MOHAMED 192300418

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13.YOUSSEF MOSTAFA 192300373 14.YOUSSEF SAYED 192300345

Introduction

The Delta Robot delivers all three. factories don’t need hands - they need speed, accuracy, and intelligence.

In this project, we designed a high-performance robotic system capable of detecting colours, gripping objects, and placing them with precision, showcasing how parallel motion mechanisms can boost automation efficiency.

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Problem Statement

• A Delta Robot uses three synchronised parallel arms to achieve fast, lightweight, and precise motion.
• In our project, this mechanism detects object colour, grips items, and sorts them autonomously — turning simple handling into smart, high-speed automation.

The goal is not just to move objects, but to move them intelligently. This project aims to design and implement a Delta-based robotic system that can:

• Detect object colour, Decide where it belongs and pick-and-place it autonomously with speed and precision. By merging mechanical design, sensing, and embedded control, The objective is to demonstrate how compact parallel robots can perform sorting tasks reliably, efficiently, and without human intervention.

Project Objective

The Delta Robot uses three synchronized arms to move with high speed and precision.

In our project, it detects object colors using an ESP-CAM, grips the items with a servo-based end-effector, and automatically sorts them into the correct location.

This demonstrates a fast, accurate, and intelligent automation system.

Delta Robot Concept

The Delta Robot system combines:

• Parallel mechanical motion
• Color sensing
• Microcontroller decision logic
• Servo actuation
• All working together to detect and sort objects autonomously.

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System Architecture

The robot was modeled in SolidWorks, focusing on speed, stability, and precise motion.

Its parallel arm structure reduces inertia and supports smooth, accurate end-effector movement, enabling reliable pick-and-place performance.

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Mechanical Design

The system uses a microcontroller to drive four servos and a servo driver, three for motion and one for gripping, executing synchronized movements based on sensor feedback to run autonomous pick-and-place actions.

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Electronics and Control

The software loop:

Detect → Classify → Decide → Move → Reset

transforming sensor input into real-time robotic action.

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Software Workflow

The AI model detects whether an object is red or blue, sends the classification to the controller, and triggers the robot to pick and sort it, enabling vision-based autonomy.

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AI Colour Detection

Mechanical design, sensing, and control software were combined and tuned to operate as one unit.

Servo motion was synchronized with color detection outputs, allowing the robot to see, decide, and act seamlessly, resulting in reliable autonomous sorting during testing.

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Integration Phase

During testing, the robot successfully:

• Detected object color in real time
• Gripped and lifted items using the servo-based end-effector
• Sorted red and blue objects into their designated positions
• The demonstration proved that the system can sense, decide, and act autonomously, achieving fast and reliable pick-and-place performance.

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Demonstration and Result

Demonstration and Result

THANK

YOU

Faculty Dean

M. Talaat