🤖 IOT_BASED_ROBOTIC_ARM

A Brain-Controlled Interface (BCI) based robotic arm using ESP8266 & PCA9685.

🚀 Project Overview

IOT_BASED_ROBOTIC_ARM is a WiFi-controlled robotic arm designed to function using brain-computer interface (BCI) signals. It integrates an ESP8266 microcontroller, a PCA9685 PWM driver, and three MG996R servo motors for precise motion control.

Users can control the robotic arm via a web interface, allowing directional movements:
➡ Left, Right, Up, Down, and Reset

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🛠 Hardware Components

Component	Description
ESP8266	WiFi microcontroller to control the arm
PCA9685	16-channel PWM driver for servos
MG996R Servos (x3)	High-torque motors for arm movement
5V 5A Power Supply	Dedicated power for stable servo operation
Jumper Wires & Breadboard	Connecting components together

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🔌 Wiring Diagram

Connections Between ESP8266 and PCA9685

PCA9685 Pin	ESP8266 Pin	Purpose
VCC	3.3V	PCA9685 logic power
GND	GND	Common ground
SDA	D2 (GPIO4)	I2C Data
SCL	D1 (GPIO5)	I2C Clock

Servo Power Connection

• V+ (PCA9685) → External 5V Power
• GND (PCA9685) → Common GND
• Servos connected to PCA9685 channels (S1=0, S2=1, S3=2)

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💾 Software Setup

Required Libraries

Install these libraries in Arduino IDE:

• Adafruit PWM Servo Driver
• ESPAsyncWebServer
• ESPAsyncTCP

Uploading the Code

1. Open ESP8266.ino in Arduino IDE.
2. Connect ESP8266 via USB.
3. Select Board: NodeMCU 1.0 (ESP-12E Module).
4. Click Upload (✓).

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🌐 Web Interface Controls

Users can control the arm using the web interface:

Button	Servo 1 (Clutch)	Servo 2	Servo 3
Left	90°	180°	0°
Right	90°	0°	0°
Up	90°	90°	90°
Down	90°	180°	90°
Reset	0°	90°	90°

Accessing the Web Interface

1. Power on ESP8266.
2. Connect to ESP8266 WiFi network.
3. Open browser → Enter ESP8266 IP Address.
4. Click buttons to move the robotic arm.

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⚡ Troubleshooting

Issue	Cause	Solution
Servos not moving	Power issue	Use 5V 5A power supply
Jittery movement	Weak ground connection	Check GND wiring
Web page not loading	ESP8266 IP address changed	Find IP in Serial Monitor

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🎯 Future Improvements

🚀 Integrate EEG-based brain control (BCI signals).
🚀 Add WebSockets for real-time movement control.
🚀 Use AI-based gesture recognition for automation.

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VID-20250207-WA0001.mp4

📜 License

This project is open-source under the MIT License.NB: Wihtout my permission no one can change or use it.

👨‍💻 Developed by: [Nishat Vasker]
📧 Contact: nishatvasker@gmail.com

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