Sensors

I looked into what would be the essential parts my new robot will need in order to learn balancing and move around. I decided I will need a gyroscope with accelerometer. The gyroscope will help provide orientation while the accelerometer will provide momentum. Knowing momentum will be used to determine how strong of a correction the robot will need to make when it sense a change in movement.

Frame

Next I would need to construct a lightweight frame. I spent a lot of time in this area. There are so many ways I could try to make it. I went with making the frame out of aluminum bars. This provided a cheap, lightweight, strong, and easy to work with material. Instead of actually engineering the frame, I can sketch up a concept and make the parts as I go.

The overall concept was modeled after a robot toy. I looked at each body part and the relative ratio to one another. I then thought about the amount of freedom each joint would need. During my research I saw others do as little as 16 degrees of freedom (DOF) to 28. I decided to start with 20 DOF for this robot. Some joints have 1 degree of motion like the knee and others have 3 degrees like the hip. I will add more later as I the robot progresses.

The hardest part of making the frame was linking multiple servos together. In the image above you can see the servos come with gear on one side. To make a stable connection each servo need a frame. The frame creates a second connection point on the back side of the servo. Below you can see the knee joint servo with a frame and leg extension attached.

The knee joint is relatively easy to make, but when I got to joints with 2 or 3 DOF. It got a lot more complicated. To keep the joint size as small as possible multiple servos will need to be combined into one part. Below is how I combined 2 and created a 2 DOF. Then when adding a third became nearly impossible. To make it work I had to attach it to the end of one. This depended on how I wanted the joint to function and where it made the most sense for this third axis.

Then comes the feet. I decided to go with wood on this, since it was easier to attach wood than created another custom metal frame. It ended up looking more like sandals than feet.

Putting it all together was the fun part. Took quite a bit of time to assemble and adjust things as needed. Yes the the robot is still missing a head and has no spine movement. Those would be future addition. The next part of this series will be the electronic portion. Where I will show how I wired up all the servos and control system. I hope the servos will be able to handle the weight of this design. If not then I am going to need bigger servos!

I hope you all look forward to my finished project. My goal is to have the robot learn to stand up and walk on its own. Then progressively add interactive features to it.

Resources

Servo

• https://learn.adafruit.com/circuitpython-essentials/circuitpython-servo
• https://learn.adafruit.com/adafruit-16-channel-servo-driver-with-raspberry-pi/hooking-it-up

Gyroscope + Accelerometer

• https://learn.adafruit.com/mpu6050-6-dof-accelerometer-and-gyro/overview
• https://learn.adafruit.com/mpu6050-6-dof-accelerometer-and-gyro/python-and-circuitpython

Parts

• https://www.adafruit.com/product/155
• https://www.adafruit.com/product/3886
• https://www.adafruit.com/product/815

The post Making the Humanoid Robot Part 2 appeared first on Botmation's personal blog for creating robots and ai.

Hello,

After the long holiday session I am finally back on track to start my next project. I think it’s about time I try tackling humanoid robot making. I been bouncing ideas with my kid. He originally wanted a robot dog which can play, talk, and clean up his toys. After a few weeks designing out the details then he comes back with, let’s make a transformer robot. I of course said well that sounds even more awesome than the last!

I was reading up the latest from CES this year and came upon a kick starter company that made just that. The robot is called T9 by Robosen and it was originally suppose to be Optimus Prime, but I assume they didn’t want to pay royalties to Hasbro and ended up with a generic truck look. However, the functions are still there. After seeing this I starting going down the youtube rabbit hole and ended up watching humanoid robot competitions.

This is when I learned that we have come a long way from the early walking robots. I have never built a humanoid robot before, but after seeing how so many people built really agile robots I am inspired to try it for myself.
Having my own humanoid robot is one of my dreams. All sorts of ideas is flowing through my mind. I can make the robot talk, walk around the house, maybe clean up toys, and put away the groceries.
Of course all that will take a lot of time and development. Which I do not have too much of with a working full time and raising a kid. So I plan to make this a long series, but great mini stories as I go along.

Planning

To build a humanoid robot from scratch requires a ton of up front planning and research. Some things I ask myself are:

How big is this robot?
What kind of parts do I need?
How much are the parts?

How are the joints connected?
How am I going to program it?
What are the features I need it to function?
Are there a pre-made kits or instructions?
What are the current techniques for training the robot?
How do I make the robot walk?

First I looked for existing works with guides to jump start my project. I found one project with some details of how it was built. This build had 17 servos controlling multiple joints. Each servo contributes to what is referred as degree of freedom (DOF) for short. The robot also had two other key components, a gyroscope accelerometer and servo driver. The gyroscope and accelerometer will give the robot a sense of balance and force. The server driver allows multiple servos be controlled from a single interface to something like a raspberry pi.

My next steps which I will talk about in the next post, will be the design of the robot. Such as where are my joints going to be and what kind of frame will I use to put all the servos together.

The post Making a Humanoid Robot Part 1 appeared first on Botmation's personal blog for creating robots and ai.

Thinking through the idea I want the plant to be able to say something to potential residents to know the moisture level is getting low. The plant could say things like “Hello, Yo, I need water, or Ahem”

Well this sounds annoying you say? well how about adding a feature to only go off during certain times of the day? Better yet lets add facial recognition to only bug the person responsible for watering the plant.

This idea is a great spring time activity to get your futuristic talking garden you always wanted.

I have uploaded the video to my youtube page.

For this project you will need the following.

• Speaker

Optionally for facial recognition you will need the following

• Raspberry Pi Camera V2

• Jetson Nano

STEP 1 Wiring Pi

Solder the pins to the ADS1115 board and connect to raspberry pi board on the following pins.

VDD – (Rpi 3.3v)

GND – (Rpi Ground)

SCL – (Rpi pin 3)

SDA – (Rpi pin 2)

Next wire the moisture sensor

VCC – (Rpi 3.3v)

GND – (Rpi Ground)

Aout – (ADS115 A0)

Once the wiring is complete go ahead and hook up the usb audio adapter and speaker.

STEP 2 Run the code

Power up the raspberry pi.

Go to my github page and get the latest files for this project. Download the Plant.py file for the raspberry pi.

https://github.com/Botmation

You should now see current reading from the sensor. In the air you may see values above 1200. If you dip the sensor into water you will see values below 600.

The code also includes mqtt function which listens for alerts from the nano. This is optional and won’t interfere if you do not have the nano.

Facial Recognition with Nano

If you like to use the facial recognition feature download the nano.py from github site.

For initial setup of the Nano please watch my video which walks you through the setup and training the program to recognize your face.

Once you train the program you can then run the Nano.py using the trained file as reference.

You will need to edit the code and update the network IP address to point to your raspberry pi.

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