Miyagi Say, “Balance Good, Everything Good”

Video

This video is Proof of Concept for my very own self balancing robot. It uses an mpu-6050 for position sensing and uses a pair of DC motors to perform the balancing.

How balance is realised

How balance is realised

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DC Motor Control Class for Arduino

One of the most rewarding aspects about building robots is understanding and designing individuals components, getting them to work and finally putting everything together into a more complex machine.

DC motor control under test

DC motor control under test

One of the key design aspects I am trying to learn is component re-usability. I don’t know what the technical term for this is, but in essence it means that I need to build components that are generic and can be reused in different robots with little or no modifications needed. This concept is very similar to Classes in Object Oriented Programming, something that I am trying to learn as well.

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Gyroscopes, Accelerometers and the Complementary Filter

How Balance Works:-

In teaching a robot how to stand straight and not fall over, we need to understand how balance really works. Balance is something we take for granted in our daily lives, most of us are actually pretty good at it, until we have had a little too much to drink.

Here is how I think balance (writ easy) works:

1. We need a sensor that tells us how ‘upright’ we are standing. In humans, this sensor is located in the inner ear. In a robot, we could use a sensor like the MPU6050 which can be used to provide tilt in two axes just by directly reading from its registers.

MPU6050 from Invensense. 6 DOF sensor that can be used to determine attitude

MPU6050 from Invensense. 6 DOF sensor that can be used to determine attitude

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Arduino Serial Communications with Qt: Better and Faster

In this earlier post, I had documented a Serial Communications Class for data transfer with an Arduino device in the Qt environment. While it worked OK for transferring data at slower data transfer rates, it couldn’t handle fast communications with the the Invensense MPU6050 IMU. Also, that version had a lot of other problems:-

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Belay That Photon Torpedo Order!!!

This post is about the application of Conditional Probability and Bayes Theorem in target detection by a randomly maneouvering search platform. Most tutorials about Bayes Theorem on the internet deal with issues like cancer detection maths or picking coloured balls from a hat. I needed a little bit more realism in my quest to understand Bayes Theorem and so I devised the following scenario.

It has taken my small brain months, maybe even years to begin to comprehend Bayes Theorem so don’t be disheartened if you can’t understand this post right away. Keep at it, keep reading, and like me, one day, the truth about our beliefs and the way we form them will dawn on you!!

I have chosen to write this post as a work of fiction rather than a paper on the subject it really addresses. In a nutshell —> Just because your sensor has reported a target detection, it doesn’t mean that there is actually a target there. Continue reading