JARVIS Ironman

Have you ever fathomed having your very own humanoid robot which could recognize faces, detect your emotions, listen to your voice commands, and respond in natural interactions? The following project describes one step-by-step process in making a humanoid robot that would be able to perform these feats, along with many more. Using powerful software tools, AI models, and a brain of a Raspberry Pi, your robot will come alive with features of speech recognition, emotion detection, object identification, and real-time interaction.

Whether a robotics enthusiast or a beginner diving into the AI and robotics worlds, this project will provide skills and knowledge that help create a smart, human-like companion of your own.

1. raspberry pi 4
2. raspberry pi camera module (V2)
3. speakers (USB)
4. mic (USB)

If you wanna make a body for your robot, you can make your own Ironman helmet, I’ve used this helmet because I wanted the body of my robot to look cool and attractive, I’ve used cardboard, epoxy resin and dry wall, you can follow this step if you want to make something exactly like mine, or you can skip this step if you choose not to create a body and use only raspberry pi and speakers.

step 1: cut cardboard into the shape you want

step 2: apply epoxy resin on it to make it sturdy

step 3: apply drywall and smooth out the texture

step 4: once the dry wall looks white and has a smooth texture paint it with spray paint

step 5: if you don’t wanna use spray paint, you can use normal acrylic paint

after following these steps, you can have your Ironman helmet ready. I have uploaded a template below for the Ironman helmet.

Assemble the components like how I assembled them, if you’re not using the same body as I did, just use a plain plank and place the speakers, raspberry and make sure the camera is pointing your face.

1. Gather Your Hardware

Before setting up your Raspberry Pi, ensure you have the following:

• Raspberry Pi 4 (recommended)

• MicroSD Card (64GB)

• MicroSD Card Reader

• Power Supply for Raspberry Pi

• HDMI Cable and Monitor

• USB Keyboard and Mouse

• USB Microphone

• USB Speaker or Audio Jack Speaker

• Raspberry Pi Camera Module

• Power

2. Flash Raspberry Pi OS

1. Download the Raspberry Pi Imager from the official Raspberry Pi website (https://www.raspberrypi.org/software/).

2. Insert the MicroSD card into your computer using a card reader.

3. Open Raspberry Pi Imager:

• Choose OS: Select “Raspberry Pi OS (32-bit)” or “Raspberry Pi OS (64-bit)” based on your project’s needs.

• Choose Storage: Select your MicroSD card.

4. Click Write and wait for the OS to be flashed onto the MicroSD card.

3. Boot the Raspberry Pi

1. Insert the MicroSD card into the Raspberry Pi.

2. Connect the monitor via HDMI.

3. Attach the keyboard and mouse.

4. Plug in the power supply to turn on the Raspberry Pi.

5. Follow the on-screen setup instructions:

• Connect to a Wi-Fi network.

• Set up your country, language, and timezone.

• Update the Raspberry Pi OS when prompted.

4. Enable Required Interfaces

1. Open the Raspberry Pi Configuration tool:

• From the desktop, navigate to Preferences > Raspberry Pi Configuration.

2. Go to the Interfaces tab and enable:

• Camera: For the Raspberry Pi Camera Module.

• I2C: For Arduino communication (if needed).

• SPI and Serial: For other hardware communication.

3. Click OK and reboot.

Required Libraries and Installation Commands

First create a virtual environment.

Install All Libraries at Once (not recommended)

pip install nltk opencv-python gtts face-recognition torch torchvision speechrecognition numpy pillow

Library Breakdown and Installation Commands

Natural Language Processing (NLP):

pip install nltk

Computer Vision (Image Processing, Face Recognition):

pip install opencv-python

Text-to-Speech (Google TTS):

pip install gtts

Face Recognition:

pip install face-recognition

PyTorch (Machine Learning Framework):

pip install torch

PyTorch Vision Utilities (Image Transforms, Models):

pip install torchvision

Speech-to-Text (Speech Recognition):

pip install SpeechRecognition

Numerical Computations (Used in Face Recognition & ML):

pip install numpy

Image Processing (Used in PyTorch Transforms):

pip install pillow

Additional System Dependencies

For Camera Access (libcamera)

Ubuntu/Debian:

sudo apt install libcamera-tools

Raspberry Pi:

sudo apt install libcamera-dev

For Audio Playback (mpg321)

sudo apt install mpg321

For face-recognition Dependency (dlib)

Ubuntu/Debian:

sudo apt install cmake

pip install dlib

While installing cmake and dlib the raspberry pi freezes and you don’t need to worry about it, it is just downloading all the stuff. Just give the systems time to download all the dependencies it needs. It may take around 20-30 minutes so sit tight and relax.

Create python files using:

nano robot_interaction.py

nano chatbot.py

nano capture_face.py

nano train_face.py

nano capture_emotion.py

nano emotion_train

How to access?

once you’ve made these files, access them using

python3 robot_interaction.py

make sure you write the python3 before the file name and then the file opens up, copy paste my code in it once you do it.

the document below provides the code for robot_interatcion.py and chatbot.py. I will update the remaining codes when I’m free and I’m still working on object detection since it requires a lot of storage space up to 128gb. Feel free to ask me questions