initial commit

README.md

+Intro to intro
+--------------
+These tutorials will cover some of the basics of the software stack 
+typically used in robotics engineering (Linux, Python), and my library for robot
+control. 
+
+The intended audience are mechanical engineering students 
+at Lund university/LTH. This translates to assuming
+experience in programming and to knowing bachelor level 
+engineering mathematics (calculus, linear algebra etc).
+The primary purpose is to get students up to speed with the 
+software needed for student projects,
+but they can be used for anyone who wants to get started with
+the mentioned topics or see what they're about.
+
+The videos are separated so feel free to skip 
+the parts you're familiar with. I do recommend watching
+or at least skipping though all of them 
+to ensure you know the specifics.
+
+The tutorials are meant to be bare-bones and used 
+just to get your feet wet.
+The idea is to introduce the absolute minimum number of concepts,
+and to empower you to learn the rest as you go.
+
+In particular we will cover,
+
+1. Linux Linux CLI basics
+============================
+     1.1. why Linux - 1 video
+          - no other option
+          - open source
+          - is the best: fastest and most robust
+          - OS itself is customizable for a task
+          - can be server - example: ai training
+          - can be raspberry pi - example: chalmers car
+     1.2. Linux as a daily driver - 1 bonus video
+          - blazing fast: example - old hardware
+          - easily customizable: distributions
+          - pretty: r/unixporn, wal color changing
+          - tailor-made workflows (ex. no mouse like my setup)
+          - random cool stuff: kde connect
+     1.2. GNU/Linux system outline, terminology - 1 video
+          - users (root vs other)
+          - package manager
+          - absolute and relative paths
+          - everything is a (text) file
+          - terminal emulator
+          - shell
+     1.3. CLI most basic commands 
+          - sudo
+          - apt - example update and install htop  
+          - ls
+          - --help - example: use ls -l
+          - cd
+          - pwd
+          - grep
+          - empowerment points:
+              - example reading error messing (bad install)
+              - man
+     1.4. advanced basics: - 1 bonus video
+          - piping
+          - forming a script
+          - using git (cloning, add, commit, push, pull (example in docker)) - 1 bonus video
+     1.5. networking - 1 bonus video, needed for robot control
+     1.6. vim
+          - just do vimtutor and look at my keystrokes
+          - :help something is very well written and useful
+          - vim - editing at the speed of thought is book if you want to be an expert
+
+2. Python
+===========
+    2.1. basic facts - 1 video
+         - made for quickly writing short code and prototyping (fast for user)
+         - very slow (for the computer)
+         - strong dynamic typing
+         - no compilation 
+         - executes one command at a time
+         - huge number of available packages
+    2.2. script vs shell + jupyter-notebooks
+    2.3. variables
+    2.4. types
+    2.5. built-in data structures: 
+         - list (dynamic linked list)
+         - dictionary (key-value hashmap)
+    2.6. loops
+         - for
+         - iterators
+         - while loop
+    2.7. functions
+         - chunk of code to be reused
+         - input/output (API) NOT ENFORCED
+         - lists are ONLY PASSED BY REFERENCE
+    2.8. classes
+         - associations of data and functions
+         - have some predefined functions like __init__, 
+            __hash__, __str__, __ge__,...
+         - only public atributes
+    2.9. many many more things
+         - list comperhensions (actually show)
+         - sockets
+         - multithreading (not real due to GIL) and multiprocessing (real)
+         - IPC
+         - decorators
+    2.10. numpy - 1 video
+         - wrappers around fast c code
+         - vectorization into real arrays
+         - arange
+         - linspace
+         - basic math
+         - matrix multiplication
+         - matrix inversion
+         - many many more
+    2.11. matplotlib
+         - plotting numpy arrays
+         - completely intuitive for basics, can get weird otherwise
+    2.12. openCV - 1 video just for this
+         - open up the laptop camera
+         - open up ip_webcam over LAN
+         - show some basic transformations like negative
+         - show classic object detection example in action
+         - show yolov4 in action
+    2.13. scipy - go over - 1 video, other libraries
+         - many many things
+         - linear algebra
+         - optimization
+         - regression
+         - ...
+    2.14. other noteworthy packages
+         - sympy
+         - scikit-learn for classic ML
+         - pytorch for neural networks
+         - pandas for tables (eats SQL, Excell, csv no problem)
+         - yolo-v8 - the end all be all of CNN based object detection
+         - control - classic control
+
+3. ur_simple_control
+======================
+    3.0. basic info - 1 video
+         - alternative to ros (less generalization, less code, more math)
+         - intended users are mechanics engineering students,
+           i.e. people strong in engineering math, but no necessarily software engineering
+         - exposes the math
+         - nearly exclusively based on reading the state and sending speed and torque commands
+    3.1. Docker - 1 video
+         - basically Linux virtual machines
+         - but can be combine with the host (internet access, memory,...) -> VERY fast
+         - images vs containers
+    3.2. ur_simple_control - 1 video
+         - pure python, will get rewritten to C++ with python bindings in the future
+         - atm only UR5e is supported, but other robots will be added
+         - every parameter is an argument
+         - RobotManager
+             - handles I/O with the robot for you
+             - manages pinocchio in step()
+             - just call step and use getters
+         - ControlLoopManager
+             - first show the math, explain partial, then go into ControlLoopManager
+             - does book-keeping around your control loop math
+             - ensures timing is right
+             - manages real time visualization and plotting
+             - handles killing of the program
+         - visualization
+             - meshcat server, handled by separate process
+         - real-time plotting
+             - matplotlib base, handled in separate process
+             - can plot whatever vectors you give it, just send an example in a dictionary
+         - logging
+             - select what you want to track by providing an example dictionary
+             - saves the entire run (dictionary of vectors) as a pickle,
+               along with the pickle of the arguments used
+    3.3. pinocchio - 1 video
+         - look at their documentation, do their tutorials if you want more
+         - data and model
+         - load robot as urdf
+         - lie algebra 
+         - body vs space frames
+         - cheatsheet overview
+         - forwardKinematics 
+         - just mention dynamics calls
+    3.4. clik math - 1 video
+         - write the equations down
+    3.5. clik in code
+         - just go over the code and explain it line by line
+    3.6. all examples run in the robotlab --> need help to film that

intro/intro_to_intro.md

+Intro to intro
+--------------
+These tutorials will cover some of the basics of the software stack 
+typically used in robotics engineering (Linux, Python), and my library for robot
+control. 
+
+The intended audience are mechanical engineering students 
+at Lund university/LTH about to do robotics projects. This translates to assuming
+experience in programming and to knowing bachelor level 
+engineering mathematics (calculus, linear algebra etc).
+The primary purpose is to get students up to speed with the 
+software needed for student projects,
+but they can be used for anyone who wants to get started with
+the mentioned topics or see what they're about.
+
+The videos are separated so feel free to skip 
+the parts you're familiar with. I do recommend watching
+or at least skipping though all of them 
+to ensure you know the specifics.
+While I did try to make them separable, 
+some topics are introduced on the go and might
+not follow the outlined order.
+
+The tutorials are meant to be bare-bones and used 
+just to get your feet wet.
+The idea is to introduce the absolute minimum number of concepts,
+and to empower you to learn the rest as you go.
+Before introducing each topic, I will also briefly
+summarize why a particular piece software has been selected.
+
+In particular we will cover:
+
+1. Linux, Linux CLI basics
+==============================
+1.1. why Linux - 1 video
+1.2. Linux as a daily driver - bonus video
+1.2. GNU/Linux system outline, terminology - 1 video
+1.3. CLI most basic commands 
+1.4. advanced basics: - 1 bonus video
+  - piping
+  - forming a script
+  - using git (cloning, add, commit, push, pull (example in docker)) - 1 bonus video
+  - networking - needed for robot control
+  - vim the text editor
+
+2. Python
+===========
+2.1. basic syntax and usage
+2.2. common packages
+2.10. numpy
+2.11. matplotlib
+2.12. scipy
+
+3. ur_simple_control
+======================
+    3.0. basic info - 1 video
+    3.1. Docker - 1 video
+    3.2. ur_simple_control - 1 video
+    3.3. pinocchio - 1 video
+    3.4. inverse kinematics theory and implementation - 1 video

linux/01_why_linux.md

+# why linux for (robotics) engineering?
+----------------------------------------
+0. there are no other options (same for ai)
+1. open-source
+   - knowledge -> guarantees
+2. it is the best: fastest and most robust
+3. customizable in size and functionality, examples:
+   - web server
+   - cloud
+   - literally every supercomputer runs Linux
+   - raspberry pi on robot - example: chalmers car
+--> it's your host computer that's the exception,
+    this simplifies life drastically
+--> it's the same system, learn it once know it for all cases
+4. best CLI
+
+# why CLI?
+----------
+0. no GUI on server or raspberry pi --> example: ssh into something
+1. gives errors
+2. everything is text, you're closer to the truth
+3. you can program the computer itself
+4. the only path to a script is writting the commands into a file
+

linux/02_linux_as_daily_driver.md

+# why linux as a daily driver?
+------------------------------
+0. there are only two reasons why you don't have it
+    0.1. some apps and games aren't ported
+    0.2. it's not preinstalled when you buy a computer
+    0.3. you can dual-boot and have the other os too
+1. it just works
+    1.1. you decide when to update
+    1.2. works better and faster than competition - fast even on old hardware
+    1.3. even if you blow it up, you can reinstall everything in an hour
+    1.4. every problem is fixable
+2. you control it
+    2.1. don't like something - remove it, replace it
+    2.2. want something - install it, it's free
+    2.3. no viruses if you don't install them
+3. infinite customizability
+    3.1. it can look like anything
+    3.2. your workflow can be whatever you want,
+         you don't even know what's possible yet
+4. everything is a text file
+5. any sequence of commands can be put into a script,
+   and that can be put on a keybinding or a cron command

linux/03_CLI_basics.md

+1.3. CLI most basic commands 
+    - sudo
+    - apt - example update and install htop  
+    - ls
+    - --help - example: use ls -l
+    - cd
+    - pwd
+    - grep
+    - empowerment points:
+        - example reading error messing (bad install)
+        - man

python/python_common_packages.md

+2.10. numpy - 1 video - do everything in the shell
+     - wrappers around fast c code
+     - vectorization into real arrays
+     - arange
+     - linspace
+     - basic math (addition, powers, exponentials)
+     - matrix multiplication
+     - matrix inversion
+     - many many more
+2.11. matplotlib - plot a sin wave
+     - plotting numpy arrays
+     - completely intuitive for basics, can get weird otherwise
+     - show matplotlib gallery
+     - show chalmers SCS labs
+     - show manipulability_visualizer
+     - show AR car
+2.12. openCV - 1 video just for this
+     - open up the laptop camera
+     - open up ip_webcam over LAN
+     - show some basic transformations like negative
+     - show classic object detection example in action
+     - show yolov4 in action HUMRO project, mention openpose
+2.13. scipy - go over - 1 video and other libraries
+     - linear algebra
+     - optimization
+     - regression
+     - ...
+     - show chalmers nonlin lab optimization example (just code and plot is ok)
+     - show a more detailed IK example (math first, then code, but very quickly)
+2.14. other noteworthy packages - just show websites
+     - tkinter - mention its shown use in manipulator_visualizer and hand detection
+     - sympy - example: calculate hessian: /home/gospodar/chalmers/NONLIN/lab/simpy_lab1.py 
+     - scikit-learn for classic ML
+     - pytorch for neural networks
+     - pandas for tables (eats SQL, Excell, csv no problem)
+     - yolo-v8 - the end all be all of CNN based object detection
+     - control - classic control

python/python_standard_library.md

+## python general
+Easiest possible language to use. Trades off
+execution speed for ease of use.
+Indentation has programatic meaning.
+Learning more syntax sugar leads to much 
+more readable code.
+
+
+### basic facts:
+- made for quickly writing short code and prototyping (fast for user)
+- very slow (for the computer)
+- strong dynamic typing
+- no compilation 
+- executes one command at a time
+- huge number of available packages
+
+
+### script vs shell + jupyter-notebooks
+- ipython is great quickly verifying things like types or math
+- a script is just a full program
+- notebooks are in-between the two and some people really like them
+  --> show a jrnh tutorial
+
+### variables
+Any variable in Python can store any type.
+The comperhensive list of types can be found at [link_to_structs_in_standard_lib]
+Here is a very short list of basic facts:
+- all variables are variable/dynamic
+- **NOTE: a variable ONLY POINTS TO A LIST, and assigning it to a different variable
+  DOES NOT COPY THE LIST by default **
+
+### data structures
+There are a number of built-in data structures in Python.
+The comperhensive list of built-in data structures can be found at [link_to_structs_in_standard_lib]
+
+#### lists
+- look like [item_1, item_2,...]
+- all lists are mutable (changeable)
+- you can put anything in a list, i.e. item_n can be of any type
+  in any list (including other lists)
+
+#### dictionaries
+- look like {key_1 : value_1, key_2: value_2, ...}
+- all dictionaries are mutable (changeable)
+- you can put anything in a dictionary
+
+### loops
+Repeat a block of code. They can be prematurely
+stopped with break .
+A chunk of code can be skipped with continue .
+
+#### for loop
+goes over an iterator. That could be
+a sequence of numbers like range(n),
+but also elements of list or dictionary etc.
+continue and break to control the loop.
+
+**example**: range, iterating over list, iterating over dictionary
+
+#### while loop
+runs as long as the logical requirement is met
+
+```python
+while test_true:
+    [code]
+```
+
+**example**: optimization until convergence (just minus something iteratively for show)
+
+### functions
+A function is a chunk of code to be easily accessed in multiple different places.
+To be used somewhere else, its inputs and the outputs need to be matched
+by the calling code. 
+**NOTE: function I/O types are not strictly enforced in Python. BE CAREFUL because
+if you don't put in what you think you're putting in,
+the code will run and you will get VERY WEIRD ERRORS.**
+
+```python
+def something(arguments):
+    [code]
+    return [any_variable]
+```
+
+example: write a theta to SO2 function
+
+### classes
+Classes are collections of variables and functions
+that help us organize our code.
+
+**example**: /home/gospodar/lund/praxis/software/double_pendulum/src/python/double_pendulum/model
+double pendulum and related functions
+
+- have some predefined functions like __init__, 
+__hash__, __str__, __ge__,...
+- inheritance exists