Many websites use bots to automate tasks and add useful (and sometimes harmful) functionality. For instance, there are reddit bots that can help you stabilize shaky videos, remind you of events or even vote on the usefulness of other bots. Telegram - an instant messaging service similar to WhatsApp - lets you create and manage bots on their platform using their Bot API. Bots on Telegram are officially identified and provide fun and useful services.
Introduction Over the last year or so, I’ve been playing around with functional programming. As the first few lines of the Wikipedia page suggest, functional programming is all about expressing a computation or algorithm as the composition of functions rather than using a state that changes over time. From what I’ve understood so far, functional programming is based on lambda calculus which is an alternative but equivalent formulation of the famous Turing Machine that most modern computers are based on.
As I mentioned in my first article on this blog, I’m now using Hugo, the static site generator to build my personal website. Due to the needs of my work environment (mostly because I need to use MS Word and certain MATLAB features on a regular basis), I’ve been primarily using Windows as my operating system for the past year or so. Having used Linux for a long time, I definitely missed the conveniences offered by shell scripting and other command line tools.
When prototyping programs that deal with lots of data on an Arduino and other embedded systems or even on full blown computers, it’s really useful to have a quick tool for plotting the output of the program. Initially, I used python for doing this. Python is a beautifully simple language and between Numpy, Scipy and Matplotlib, you can do pretty much anything you want with data; from doing simple plotting to running machine learning algorithms on the data.
Over the past few months I’ve been spending a lot of time on implementing various signal processing algorithms in C/C++. Things like Kalman Filters, various types of FIR filters and finite state machines. The number of steps needed to implement each these algorithms were fairly small and in the beginning I tried to put all the functionality of these implementations into simple to use C++ classes. This made things look neater and also fit in quite well with the Arduino programming framework (I was implementing a lot of these algorithms on Arduino compatible microcontrollers like the Teensy).
Xenomai gets tasks to run in real-time by having a co-kernel running alongside the regular linux kernel handling all the time critical tasks. The Xenomai co-kernel is able to do this because of the i-pipe patch that the custom kernel is compiled with. This patch adds an interrupt pipeline that sits between the hardware of the computer and any kernels running on the hardware. The interrupt pipeline has domains which can be assigned a priority.
In my lab, we recently started moving away from Simulink’s Real-Time packages and towards Real-Time Linux for implementing the low level control of our robots. I thought I would document what I went through to get Xenomai (A Real-Time framework for linux) working stably as a resource for others trying to get started on the same thing.
What is Real-Time? The word “real-time” is used in a lot of different fields to mean different things.