emerging-mind.org, eJournal ISSN 2567-6466
Email: info@emerging-mind.org
Author: Gerd Doeben-Henisch
gerd@doeben-henisch.de
(August 11, 2022, latest change: August 14, 2022)

CONTEXT

This Text is an example located in the List of examples for the raspBerry Pi experimental board.

My Real Story: Start a raspBerry Pi board

(Last change: 14 August 2022, 08:23h)

Triggered by an interesting master thesis of a student writing about a Robo-Car which is using a raspBerry Pi experimental board, I decided to start myself with some experiments.

Instead of starting directly with the raspBerry Pi organisation [1] I checked the internet and came up with a package like this: STUUC Raspberry Pi 4 Model B 8GB Ram with 32GB Memorycard, Raspberry Pi 4B Kit with Quad-Core A72 supporting Dual Display 4K/WiFi 2.4G.5G,LAN 1000Mbps/ BT 5.0/USB3.0 all Parts included.

This was all I had; no further explanations. To put all these parts together, purely mechanically, wasn’t such a problem. But this is not what you want. You want a working computer. With the following steps it worked out nicely:

I put the cooling elements (the ‚heat sinks‘) on the determined parts by pressing them onto the surface, after I have pulled the protective layers off.
I put the board into the ground cover.
Then I put the micro-SD card (32 GB) into a small slot left on the board (there is only one) with the inscriptions of the SD card below (otherwise it will not enter the slot).
Then I inserted the power supply in the USB-C slot, the screen with the HDMI cable to the left micro HDMI slot, the mouse and the keyboard to the 2 left USB-2 slots.
Then I attached the middle cover on the board.

raspBerry Pi experimental board with ground- and middle cover. Left the USB-C connector with the power supply, one micro-HDMI connector with the screen, and the two USB-2 connectors with the mouse and the keyboard.

Then I switched the experimental board on.
The screen became active but the text appearing on the screen told me, that the software is too old, and this message started to repeat …
I pulled the micro SD card out again, transferred it with an SD-card adapter into an old SD-card reader, connected it to my unix-machine (a windows machine would also work) and activated the raspBerry site where the raspBerry Pi software is described.[2]
From this site you can download the ‚Raspberry Pi Imager‘ which is a very nice program. If You start it (linux as well as windows) you can download the newest version of the raspBerry Pi operating system on your SD card, pull them out and insert it again in your raspBerry Pi board.
Starting again with the new version, now it worked fine. Connected to the internet via Ethernet or Wlan you can update everything and then you can start working.
With the free USB-3 connectors you can connect other SD-card memories or even large USB-drives … and much more.

Adding a camera

For the experiments-chapter I will need a camera. Here you can get first information about the raspberry Pi’s cameras. I decided to take the new camera which offers a lot of capabilities.

The raspberry Pi camera module 2 with 8 MP (Mega-Pixels). I took the photo from the new camera with my smartphone, connected the smartphone with an USB cable to the raspberry Pi board and copied the photo onto the raspberry Pi. On the raspberry Pi I could format the Photo with the free gimp-software (which is not really necessary, but helpful) and loaded it up with my word-press blog software.

The specialty of the raspberry Pi’s cameras is that these are fully integrated in the hardware and software of the raspi.This enables completely new applications compared to a ’normal‘ camera which is only attached by an USB connector. This full integration is possible because there exists a whole bunch of software called in the older version ‚raspicam‘, now ‚libcamera‘, which can be used to work with the signals of the camera. The original sources for the camera are written in C++, but the user can interface with the camera by so-called camera-apps which offer complex functions for direct use, and one can write own camera-apps. But because the most used programming language on the raspi is the programming language python, there existed since the beginning a python library called ‚picamera‘ provided from the ‚outside‘ of the raspi development team. With the publication of the new raspberry Pi processor accompanied by a new version of the operating system (linux) called ‚bullseye‘ the old python picamera library doesn’t work any longer. One can still use it, but the future has another direction. The new ‚philosophy‘ of the rasp development team is nicely described in this ‚readme document‘ attached to the new version of the camera software called ‚libcamera‘:

„A complex camera support library for Linux, Android, and ChromeOS

Cameras are complex devices that need heavy hardware image processing operations. Control of the processing is based on advanced algorithms that must run on a programmable processor. This has traditionally been implemented in a dedicated MCU in the camera, but in embedded devices algorithms have been moved to the main CPU to save cost. Blurring the boundary between camera devices and Linux often left the user with no other option than a vendor-specific closed-source solution.

To address this problem the Linux media community has very recently started
collaboration with the industry to develop a camera stack that will be open-source-friendly while still protecting vendor core IP. libcamera was born out of that collaboration and will offer modern camera support to Linux-based systems, including traditional Linux distributions, ChromeOS and Android.“

To write a completely new camera software in python is not a simple task. Therefore it needed some time to develop it and it is still not completely finished. But, luckily, the first experimental releases are there and do already function to some extend. While the messages from the development team in November 2021 have been rather announcements only, the massages from February 2022 sound differently. Now a new — yet still experimental — software is available by download from the github server. The new name of the old picamera library is ‚picamera2‘ and it is developed now by the raspi development team directly. Here you can find a download for the picamera2 document, which describes the whole library with installation descriptions.

Here you can look to a 10s video taken with the new camera modul 2 with the new — still experimental — python library picamera2:

from picamera2 import Picamera2
picam2 = Picamera2()
picam2.start_and_record_video(„test.mp4“, duration=10)

Small 10s test video with functions of the new picamera2 python library.

configure-tool

The simplest way to configure the raspberry Pi after the installation is to call the rasp-configure tool by typing into the shell:

gerdpi@raspberrypi:~ $ sudo raspi-config

Then the following screen will show up:

If you will use the audio-jack for your headphones instead of the loudspeaker of your screen you can select on the main screen 1. System options and then

you can select S2 Audio to make your choice.

GPIO-settings

If you want later define some settings on the general input-output (GPIO) you can do this. Here is the GPIO outline:

COMMENTS

[1] See raspBerry Pi organisation: https://www.raspberrypi.com

[2] raspBerry Pi organization, software: https://www.raspberrypi.com/software/ or here, more simpler: https://projects.raspberrypi.org/en/projects/raspberry-pi-setting-up/1

some background story

Gerd Doeben-Henisch
info@emerging-mind.org
gerd@doeben-henisch.de

PDF

abstract

Some information about the motive behind this project; some historical remarks.

RELAUNCHE

This relaunch of the eJournal emerging-mind.org (ISSN 2567-6458) is motivated by an international book project rewriting the ideas of systems engineering (SE), actor-actor interaction (AAI) as part of systems engineering, as well as intelligent machines (IM) as part of AAI. There is also an introductory part which talks explicitly about the implicit philosophical assumptions which underlie a systems engineering approach in general. This book is written embedded in a public process documented on the uffmm.org website.

SOME GENERAL REQUIREMENTS

While the above mentioned book develops a strong formal framework for all the mentioned topics, such a pure formal approach is not enough. The processes described in the book are intended real processes in real environments relying heavily on software. Therefore it is an equally important question which kind of software framework can help in the application of the theory. The following requirements are considered as being important for the development of the emerging-mind lab.

AAI Theory

As one can read on the uffmm-site a radical formal approach is applied there to describe the analysis phase of systems engineering as it is realized by an actor-actor interaction approach. But for the real work this is not enough, one needs for the practical (industrial) work in the end software tools which support the formal theory to do the real work.

Intelligent Machines

Intelligent machines are analysed in the book as actor models within actor stories. Thus models can only be used as real dynamic processes if they are translated into real software within real computers. And this should be done in accordance with the AAI-paradigm.

Local Learning Environments

There is a third requirement which stems from the context of education and experimental research.

Today everybody has a computer or a smart-phone to log into some network which provides lots of services from somewhere. The network as such also the services as such are usually not open for experimental usage. But in education as well as in research one needs complex settings and one needs open structures, which can be changed.

For this one needs a local learning environment which contains its own network server with different clients (computers, smart-phones, raspi, robots, and so on) which can have more smaller clients like sensor, actors etc.

Solution Candidates

Although the search for an optimal hardware and software environment has not yet finished we have two first interesting candidates as main part of the intended structure: It is (i) the robot operating system (ROS) (see: http://www.ros.org/) running on ubuntu (actually only on the long term version 14.04), and, with a different scope, (ii) the tensorflow framework (see: https://www.tensorflow.org/).

How to Continue?

The next possible readings are:

Kategorie: ubuntu

raspBerry Pi Starter-Kit. An Example

CONTEXT