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Επικοινωνία

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7/3/2017, 20:00

European Dissidents ALARM

 

Zeppelin: Beyond Gravity

 

Foreign intervention in Greece?

 

Η ανελεύθερη Ελλάδα

 

Η Ελλάδα καταγώγιο;

 

Αν.Επ. Π. Παυλόπουλο

  

Intangible prisons

 

Plausible deniability

 

Images of German w & s

 

Crimes against Humanity

 

"Chimera" - "Bellerophon"

 

pr. Donald Trump

 

  

Legal Notice 87

 

Βδέλλες, αποικιοκρατικές

 

Being a German

 

Legal Notice 84

 

Dirty colonial methods

 

Georgi Markov, BG - KGB

 

Samples of Barbarity

 

Ελλάδα - αποκόλληση

 

Έλληνες, στο έλεος...

 

Harvester's log 16/3/17

 

 

Legal Notice 66

 

Execrable

 

Legal Notice 62

 

  

My story

 

  

Aggression?

 

  

Η Εστία μου

 

  

Why so untidy?

 

  

Αποικιοκρατία

 

  

Εξόντωση Ελλήνων αντιφρονούντων;

 

  

Ζήτημα εμπιστοσύνης

 

  

Μεθοδικότητα

 

  

Ανοικτή Επιστολή πρέσβη ΗΠΑ

Αφορμή, U2RIT vs Ελλάδα;

Βιοηθική

A request to U2RIT

Colonial aggression - 2

Open Letter to UN S.G.

Open Letter to p.C. & p. O.

Δήλωση πρόθεσης επαναπατρισμού

 

Ο "εφιάλτης" της Νυρεμβέργης

Συλλογή Φωτογραφιών

Αίτημα προστασίας, προς Ιταλία

Chroma key, background removal

Science and Ethics

Να συμβάλει και η U2RIT

Θα ξαναφτιάξουν πολλές φορές Άουσβιτς και Zyclon B

 

Split-Screen effect

Η Ζωή είναι Ωραία.

Βόρεια Κορέα

Λευτεριά στους Έλληνες, εξανα- γκαστικά "Εξαφανισμένους"

 

Μυστικές δίκες;

Trustworthiness

Πολιτισμό, ή, απληστία;

Ακραία Στυγνότητα

Η Τέχνη της Επιβίωσης

Political Asylum 3

Επιστροφή στις ρίζες

The Human Cost of Torture

An urgent appeal for solidarity

More obvious than the Sun

Western "culture"

Political Asylum

Έννομη Προστασία

Μια μήνυση που εγείρει ερωτηματικά

 

 

 

Honor your father...

Noise

Creative Greeks

A pair of Dictatorships

ROS και ρομπότ αυτόματης συγκομιδής σπαραγγιών PDF Εκτύπωση E-mail
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Συνεννόηση για Δράση - Απόψεις
Συντάχθηκε απο τον/την Χρήστος Μπούμπουλης (Christos Boumpoulis)   
Πέμπτη, 02 Νοέμβριος 2017 21:08

asp-v04-05.PNG

 

 ROS και ρομπότ αυτόματης συγκομιδής σπαραγγιών

 

Επί του παρόντος έχω διαμορφώσει την άποψη, σε σχέση με τη δομή της ρομποτικής μηχανής συγκομιδής σπαραγγιών, να κάνω χρήση του λειτουργικού συστήματος ROS (Robot Operating System) και πέντε (5) υπολογιστικών συστημάτων Raspberry Pi 3 model B (35 ευρώ έκαστο).

  

asp-v04-04.PNG

 

 

Συγκεκριμένα, η συγκεκριμένη εφαρμογή περιλαμβάνει την επεξεργασία ενός μεγάλου όγκου δεδομένων (επεξεργασία στερεοσκοπικής εικόνας και επεξεργασία δεδομένων του LiDar για την κατασκευή ενός τρισδιάστατου χάρτη της καλλιέργειας).

Εναλλακτικά, θα μπορούσε να χρησιμοποιηθεί μόνο ένα, πολύ ισχυρό, τυποποιημένο υπολογιστικό σύστημα και οι διάφοροι αισθητήρες (κάμερες, LiDar, GPS, αισθητήρας μαγνητικού πεδίου, επιταχυνσιόμετρο, κ.λπ.) να συνδεθούν σε μια εκ του μηδενός κατασκευασμένη ηλεκτρονική διάταξη διεπαφής (custom made).

  

asparagus-17-11-02.PNG

Η δυνατότητα που παρέχει το λειτουργικό σύστημα ROS για εύκολη και βέλτιστη κατανομή του υπολογιστικού έργου σε περισσότερα του ενός υπολογιστικά συστήματα, τα οποία είναι συνδεδεμένα μεταξύ τους μέσω του ταχύτατου πρωτοκόλλου επικοινωνίας Ethernet, σε συνδυασμό με, μειωμένο κόστος κατασκευής, με αποφυγή μιας χρονοβόρας και κοστοβόρας, εκ του μηδενός ανάπτυξης μιας μονάδας διεπαφής (interphase) και με αυξημένη, σε πραγματικό χρόνο, ανταπόκριση του ηλεκτρονικού μέρους της μηχανής, με οδήγησε στην επιλογή της λύσης που περιλαμβάνει τις πέντε μονάδες επεξεργασίας.

Οι τέσσερις από τις πέντε υπολογιστικές μονάδες θα είναι άμεσα συνδεδεμένες με τις 4 κάμερες του συστήματος, ενώ η πέμπτη, θα είναι συνδεδεμένη άμεσα με το LiDar και τους περισσότερους από τους υπόλοιπους αισθητήρες του συστήματος και επίσης θα διαχειρίζεται όλες τις ασύρματες επικοινωνίες (WiFi, GSM, bluetooth) και τη σύνθεση ανθρώπινης φωνής.

Κατά τη λειτουργία της μηχανής, το υπολογιστικό φορτίο θα κατανέμεται στις πέντε μονάδες επεξεργασίας με κριτήρια, το πόσο ήδη “φορτωμένη” είναι η κάθε μια μονάδα, το πόσο “φορτωμένος” είναι ο δίαυλος επικοινωνίας Ethernet, το πόσο “φορτωμένος” είναι ο εφεδρικός ασύρματος δίαυλος επικοινωνίας Wifi, και το είδος της, προς κατανομή, υπολογιστικής εργασίας.

  

 

raspberry-pi-3-model-b

 

 

Οι υπολογιστικές και τεχνικές επιδόσεις κάθε μιας υπολογιστικής μονάδας Raspberry Pi 3 mobel b είναι η ακόλουθες:

Specifications

SoC: Broadcom BCM2837
CPU: 4× ARM Cortex-A53, 1.2GHz
GPU: Broadcom VideoCore IV
RAM: 1GB LPDDR2 (900 MHz)
Networking: 10/100 Ethernet, 2.4GHz 802.11n wireless
Bluetooth: Bluetooth 4.1 Classic, Bluetooth Low Energy
Storage: microSD
GPIO: 40-pin header, populated
Ports: HDMI, 3.5mm analogue audio-video jack, 4× USB 2.0, Ethernet, Camera Serial Interface (CSI), Display Serial Interface (DSI)

Wireless radio

So small, its markings can only be properly seen through a microscope or magnifying glass, the Broadcom BCM43438 chip provides 2.4GHz 802.11n wireless LAN, Bluetooth Low Energy, and Bluetooth 4.1 Classic radio support. Cleverly built directly onto the board to keep costs down, rather than the more common fully qualified module approach, its only unused feature is a disconnected FM radio receiver.

There’s no need to connect an external antenna to the Raspberry Pi 3. Its radios are connected to this chip antenna soldered directly to the board, in order to keep the size of the device to a minimum. Despite its diminutive stature, this antenna should be more than capable of picking up wireless LAN and Bluetooth signals – even through walls.

SoC

Built specifically for the new Pi 3, the Broadcom BCM2837 system-on-chip (SoC) includes four high-performance ARM Cortex-A53 processing cores running at 1.2GHz with 32kB Level 1 and 512kB Level 2 cache memory, a VideoCore IV graphics processor, and is linked to a 1GB LPDDR2 memory module on the rear of the board.

GPIO

The Raspberry Pi 3 features the same 40-pin general-purpose input-output (GPIO) header as all the Pis going back to the Model B+ and Model A+. Any existing GPIO hardware will work without modification; the only change is a switch to which UART is exposed on the GPIO’s pins, but that’s handled internally by the operating system.

USB chip

The Raspberry Pi 3 shares the same SMSC LAN9514 chip as its predecessor, the Raspberry Pi 2, adding 10/100 Ethernet connectivity and four USB channels to the board. As before, the SMSC chip connects to the SoC via a single USB channel, acting as a USB-to-Ethernet adaptor and USB hub.

Sysbench

Offering support for multi-threaded operation – taking advantage of the four processing cores on the Pi 2 and Pi 3 – SysBench reveals just how far we’ve come since the original Raspberry Pi design. While single-threaded performance has improved greatly, the biggest gains go to multi‐threaded programs.

[www.raspberrypi.org/magpi/raspberry-pi-3-specs-benchmarks/]

 

Σχετικά με τις δυνατότητες κατανομής του έργου επεξεργασίας σε περισσότερες της μιας μονάδες επεξεργασίας, δείτε τα παρακάτω:

 

Χρήστος Μπούμπουλης

οικονομολόγος

Deep-Dive with ROS

ROS: The Robot Operating System

With a Pi installed in the head of Marty providing a substantial boost to computational power, more advanced features can be implemented. One of the best ways to leverage this extra power is through the use of the Robot Operating System - ROS. You can take advantage of the vibrant community and ecosystem that exists to learn about robots and how to develop cool applications for them.

Okay, great, but what exactly is ROS?

In essence, ROS is a flexible framework that aims to ease the development of creating robot software. It’s a pseudo operating system consisting of a wide range of software tools and libraries that make life a little easier for robotics developers. One of it’s main strengths is the open-source nature of the framework. This was intentionally designed in order to promote collaboration between groups, capitalise on their strengths and build on each other’s work, with the end result being more robust and effective robot software.

As such, individuals or groups can create their own tools and libraries and publish them for use by the wider ROS community. This modularity makes life a little easier for budding roboticists (which you most likely are if you’re reading this) as it allows you to use as much or as little of ROS as you’d like, picking and choosing what suits your particular application best.

And how does it work?

Providing an exhaustive breakdown of what is comprised within ROS would take a long time and is outwith the scope of this relatively simple introduction. You can look here for an overview of the core components, as well as an array of guides, tutorials and documentation on the ROS wiki.

Let’s cover the basics of ROS, first.

Underpinning ROS is the concept of distributed computing, and ROS itself is a kind of peer-to-peer distributed system. A ROS system - in this case not neccessarily a single machine - is a network comprising of independent nodes (synonymous with processes) that communicate with each other by passing messages, using a publisher and subscriber model. A node can essentially broadcast its data over a named bus - called a topic - to be picked up by any other node that is interested in that data. For example, a camera node can publish a stream of images, which can be picked up by another node that handles some kind of processing using the images. There is no limit to the number of subscribers a topic can have, or whether the node is even on the same machine (or architecture!).

This distributed model is really handy, and can easily span devices and operating systems. Using Marty as an example, the Rick (an Arduino based board) communicates with the Pi through serial communication, using rosserial.

I think I’m starting to get it…

Don’t worry if this isn’t making complete sense for now. Let’s visualise it. We’ll use Marty’s face tracker as an example.

It’s a simplified view, but relatively accurate. Let’s break down what’s going on here.

Governing everything, is the ROS Master. This node is crucial to the running of a ROS system, and its role is to handle the naming and registration of the other nodes in the system. It keeps an eye on the various publishers, subscribers and services that are running over the entire system. Once a node registers with the Master, it can then communicate with any other node that has registered with the Master.

Next, is the raspicam_node. This is the node that gets images from the Raspberry Pi camera and publishes it over the /marty/camera/image topic.

This data is then read by the face_tracker node by subscribing to the /marty/camera/image topic, and this node handles the image processing (such as detecting faces, eyes and smiles). Once this has been completed, this node publishes the processed images (/marty/face_tracking/faces, for example) as well as the co-ordinate data of the detected features within the image frame (/marty/face_tracking/faces_centroid, for example).

Also shown is the method of visualisation, the output of which, in this case, is simply a rectangle drawn over any detected features. This is performed on the laptop that is used in this ROS system and is achieved through running an instance of rqt_image_view on the laptop and subscribing to a video output of the face_trackernode. The Terminal here is simply a command line prompt that has been told to subscribe to the /marty/face_tracking/faces_centroid topic and prints the output.

It’s a relatively simple example, but illustrates the structure of a typical ROS application.

Worthy of note is the previously mentioned modularity of ROS. It doesn’t neccessarily have to be an on board camera that the face_tracker node receives images from, it could just as easily be a camera on the network (so long as the subscribed topic name is the same of course). Also, expanding or utilising data from this node is straight forward, simply subscribe to the relevant topic in your application and you have the data. For example, you could have a script that subscribes to the co-ordinate data from the /marty/face_tracking/faces_centroid topic and make Marty move to track your face. Try it and show us, we’d love to see!

Cool! So where do I start?

Now that the basics have been explained, diving into practical examples is next.

The official Marty Pi image already has a version of ROS installed, so you can bypass the pain that is installing ROS from source.

Before you dive in though, it is highly recommended to install ROS on another computer. This will speed up your development and just make life that much easier. Also, when it comes to developing robot applications, Linux is king, so it is also virtually a requirement to use an OS like Ubuntu. It’s one of the most widespread Linux distros and is officially supported by ROS, here’s the official install tutorial. There exists versions of ROS that can “run” on Windows and OSX, but these are still experimental, buggy and not recommended.

Once you have Ubuntu and ROS installed on a computer of your choice, my advice is to get your bearings first and follow the official ROS tutorials. These will get you familiar with the beginner level stuff that’s neccesary to get Marty to do cool things.

[https://robotical.io/learn/article/Deep-Dive%20with%20ROS/Learn/]

 

 

Σημείωση: η εικόνα βρέθηκε εδώ, www.reichelt.de/bilder/web/xxl_ws/A300/RASP_03_01.png.

 

 

Τελευταία Ενημέρωση στις Παρασκευή, 03 Νοέμβριος 2017 11:55