Machine Learning & Robotics

## Differential Equations - Simple spring model

There are usually more than one options how to get solve a problem. It is particularly true for math. Let's look on a spring and its mathematical model.

## Осцилограф С1-94 - Oscilograf c1-94 - probe input

Once I got chance to play with the USSR oscilloscope - Осцилограф С1-94. The problem was, the oscilloscope has DIN5 socket input instead of the BNC. I made following adapter:

## Kalman Filter implementation

Using processing I have implemented a 2D Kalman Filter java applet. Here are my personal notes gathered during the development:

## Inverse kinematics

Suppose you have an equation (describing for example a robot arm) that gives you a position of the end-effector (for example fingers of a robotic arm) when input like joint angles is provided. This would be Forward kinematics (FK). Opposite problem when position of the end-effector (goal) serves as input and joint angles are on output is called Inverse kinematics (IK).

## gpsim tutorial

To build a robot it is often neccesery to create also a hardware. PIC programming is one of many possible options. I have chosen this way several times and hence know a good PIC simulator is very handy. I have found difficult to find any gpsim tutorial aimed on windows version of the gpsim out there. Therefor you may find one here:

## Coordinate systems

Coordinate systems and especially transformations between local and world coordinates are used in robotics very often. Here is a small but practical introduction into the topic.

There are different types of coordinate systems but when we talk about robotic the most popular are:

## Kalman Filter

Kalman Filter is over 50 years old but is still one of the most used data fusion algorithms used today. It is a popular technique for estimating the state of a system. Kalman filters estimate a continuous state and gives a uni-modal distribution. Uni-modal = when we use KF for a robot position estimation, KF gives us only one possibility where the robot is located with a certain possibility

## LTI systems 2

After all the theory we went through in the part 1 it is time for a real design of control system. In this part we are about to design a full state feedback control system of the magnetically suspended ball.

## LTI systems 1

The very first step in the control design process is to develop appropriate mathematical model of the system derived either from physical laws or experimental data. We introduce the state-space and transfer function representations of dynamic systems. We then review some basic approaches to modeling mechanical and electrical systems and show how to enter these models into MATLAB for further analysis.

## Control of mobile robots 1

After passing the coursera.org course Control of Mobile Robots taught by a great professor Magnus Egerstedt. I have created a simulation of the differential drive robot.

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