Robot Gripper Arm Project

Overview

An electromechanical gripper arm prototype designed to assist individuals with limited mobility in performing daily tasks. The device features autonomous and adaptive gripping capabilities using force and distance feedback, with an intuitive joystick interface and built-in safety mechanisms.

Key Applications

• Assistive technology for individuals with mobility impairments
• Educational robotics and mechatronics demonstrations
• Research platform for adaptive gripping algorithms

Features

• 🤖 Autonomous Grip Control — Intelligent gripping using force and distance sensor feedback
• 🎯 Ergonomic Design — Bike-handle grip design optimised for accessibility
• ⚙️ PID Control System — Consistent grip strength regulation for delicate objects
• 🕹️ Intuitive Interface — Joystick control for precise positioning and operation
• 🛡️ Safety Mechanisms — Emergency release and force limiting protection
• 📊 Real-time Feedback — Continuous monitoring of grip force and object detection

Technical Specifications

Hardware Components

• Microcontroller: Arduino Uno R3
• Power Supply: 12V, 1A (12W) plug-in adapter
• Weight Capacity: 10g – 500g
• Object Dimensions: 15×10×10mm – 60×80×150mm

Sensors & Actuators

Component	Model	Purpose
Current Sensor	INA219	Motor current monitoring and force feedback
Distance Sensor	HC-SR04 Ultrasonic	Object detection and positioning
Force Sensor	Force Sensing Resistor (FSR)	Direct grip pressure measurement
Drive Motor	DC Geared Motor	Primary gripping mechanism
Positioning Motor	Servo Motor	Gripper rotation and alignment

Control System

• Algorithm: PID feedback control
• Response Time: <100ms sensor-to-actuator
• Precision: ±2mm positioning accuracy
• Safety Limits: Configurable force thresholds

Circuit Diagram

The circuit diagram shows the complete electrical connections between the Arduino Uno, sensors, motors, and power supply.

Quick Start

Prerequisites

• PlatformIO IDE (or PlatformIO Core CLI)
• USB Cable (Type A to Type B)
• 12V Power Supply

Installation

1. Clone the Repository

   git clone https://github.com/AdzCoder/robot-gripper-arm.git
   cd robot-gripper-arm

2. Install Required Libraries

   This project uses PlatformIO for dependency management. Libraries are automatically installed from platformio.ini:

   lib_deps = 
      adafruit/Adafruit INA219@^1.2.3
      jchristensen/movingAvg@^2.3.1
      arduino-libraries/Servo@^1.2.1

   Library	Version	Licence	Purpose
   Adafruit INA219	^1.2.3	MIT	Current sensing and power monitoring
   movingAvg	^2.3.1	GPL-3.0	Signal filtering and noise reduction
   Servo	^1.2.1	LGPL-2.1	Servo motor control

3. Build and Upload

   # Build the project
   pio run
   
   # Upload to Arduino Uno
   pio run --target upload

Hardware Setup

1. Connect Power Supply — Ensure 12V adapter is properly connected
2. Verify Connections — Check all sensor and motor wiring per circuit diagram
3. Calibrate Sensors — Run initial calibration routine (see User Manual)

Usage Guide

Basic Operation

1. Power On — Switch on main power and wait for initialisation LED
2. Position Gripper — Use joystick X/Y axes for precise positioning
3. Activate Grip — Press joystick button to engage autonomous gripping
4. Release Object — Push joystick forward for controlled release

Advanced Features

• Force Adjustment — Modify grip strength via potentiometer
• Emergency Stop — Pull joystick backwards for immediate release
• Calibration Mode — Hold button during startup for sensor recalibration

Troubleshooting

• No Response: Check power connections and Arduino USB link
• Weak Grip: Verify motor current readings and force sensor calibration
• Positioning Issues: Recalibrate distance sensor and check for obstructions

Documentation

• ⚡ Circuit Diagram — Electrical connection schematic
• 📊 PID Data — PID control system test data
• 📈 Current Filter Data — Signal filtering analysis data

Project Information

Development Team: Group J4
Institution: University of Warwick, School of Engineering
Module: ES2C6: Electromechanical System Design (2023/24)

Project Objectives:

• Design and implement an assistive robotic device
• Integrate multiple sensor systems for autonomous operation
• Develop safety-critical control algorithms
• Create accessible human-machine interfaces

Future Enhancements

Potential improvements identified during development:

• Machine Learning Integration — Adaptive grip patterns based on object recognition
• Wireless Control — Bluetooth or Wi-Fi interface for remote operation
• Multi-DOF Movement — Additional servo motors for enhanced positioning
• Visual Feedback — Camera integration for improved object detection

Contributing

This is an educational project that has been completed. However, if you're using this code for your own research or studies:

1. Fork the repository for your modifications
2. Document any significant changes or improvements
3. Consider sharing results with the academic community
4. Respect the original licensing terms

Project Status

Status: Completed (Academic Year 2023/24)
Maintenance: No longer actively maintained
Usage: Available for educational and research purposes

This project represents a successful completion of the ES2C6 coursework requirements and demonstrates practical application of mechatronic principles in assistive technology.

Licence

MIT Licence — see the LICENCE file for details.

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This project was developed as part of academic coursework at the University of Warwick. For technical questions or educational collaboration, please contact through appropriate academic channels.