-server application -remote acces via webserver -store -change -add -remove -accept a request or reject if a new request is overlapping an existing one Pentru a intra pe site puteti accesa link-ul: LEC 2017 - Reservation Request  Ne cerem scuze pentru depasirea duratei maxime a videoclipului, deja incarcasem videoclipul cand am observat existenta unei durate maxime, daca este vreo problema putem incarca alt videoclip care sa se incadreze in durata permisa.

After the project presentations, the jury will offer awards for: Exceptional Activity The possibility to be enrolled in a Freescale Internship for next year Best Project Amazon Kindle Paperwhite per each member of team                            Most Original Idea Garmin Forerunner® 10 per each member of team            

We are the team CanYouCMe and this is the video for Milestone 1 Project 1: Conveyor Belt with Optical Sorter. We will present the assembled Conveyor Belt and the object removing mechanism. The belt motion is implemented using a stepper motor and the object removing mechanism is implemented using a servo motor, both being controlled by the UDOO board, using Arduino We also added the camera which will get the images to be processed.

Am prezentat funtionalitatea proiectului. Datorita faptului ca placuta udoo ruleaza mai lent codul detector de pozitia pupilei si notificarea laptopului se face prin retea( programul detector care ruleaza pe udoo scrie intr-un fisier pozitia pupilei, dupa care o transmite prin scp calculatorului, cel din urma ruland un script care afiseaza mereu fisierul primit) am atins limita maxima(2:46) pentru fimul demonstrativ. Drept urmare, prezentarea codului constitutiv Milestone3 se afla pe repo-ul de Github , sub forma unui filmulet complet in care: prima parte reprezinta prezentarea codului iar a 2-a parte reprezinta prezentarea functionalitatii. Din motivelor de mai sus am ales sa pastram partea de prezentare a functinalitatii pentru uploadul de aici si sa facem referire fimuletul complet prezent pe GitHub.

Registration requirements Minimum skills Previous experience with C or Java is needed. Previous experience with Linux systems is needed. Experience with embedded programming is a PLUS but not a MUST. Team one to three members from either Politechnica University of Bucharest or Military Technical Academy. Judging Criteria Originality Is this something new or improving something that existed before ? Execution Does it do what it should do, are there any major issues ? Usability Is the project easy to use and/or integrate ? Utility Does it have applicability within the Automotive domain ?

The attached lecture is an short introduction about Linux BSP and developing software with Wandboard.

Pentru milestone-ul 3 am implementat algoritmul de stabilizare. Acesta fucționează dar este nevoie de mai mult reglaj înainte ca drona să poată fi capabilă de zbor. Momentan compensarea motoarelor nu este suficient de precisă, iar drona face mișcări prea bruște. În video demonstrăm cum algoritmul compensează înclinarea pe axe prin schimbarea puterii motoarelor. De asemenea se poate observa implementarea bonusului, aplicația este completă, are feedback de la dronă și afișează informații în timp real despre parametrii de zbor.

Assembly of our project using 2 servo motors, the Udoo board, and a separate voltage regulator for the power for the servo's.  We probably did something wrong. one of the servos is dead ( it seems the inside gears are damaged, we can hear it spinning, but it doesn't move on the outside. We are using cheap, plastic gears in the servo).

Aici demonstram legatura dintre semnalul preluat de la volanul pentru jocuri video si servomotoarele care controleaza farurile. Volanul este conectat prin USB, iar semnalul este preluat in procesorul Cortex A9. Este prelucrat si transmis catre coprocesorul M4 prin interfata seriala, de unde sunt actionate motoarele. De asemenea, am refacut modelul de bot de masina, care are acum un design mai realist.

In the movie, we show that we wired the necessary connections to the 'T' pin (the red wire) of the board inside the headset, and to the ground, that needs to be common with the UDOO board's ground (the black wire). The wires are connected to the 0 (RX) pin and the GND pin of the UDOO board, respectively. Software-side, we used the Brain library which takes packets received from the serial interface and interprets them, giving values in CSV form, for us to process in the next step. For receiving data from the headset, the M4 core of the board runs the Arduino code and uses the Serial0 object (UART 5) to take the raw data, which is processed by the Brain library. Then, the resulting string is sent to the A9 core by using the provided shared memory. The Serial object is used for this step, as we see in the video. The received string contains values in the following form: signal strength, attention, meditation, delta, theta, low alpha, high alpha, low beta, high beta, low gamma, high gamma We will use them in the following milestones.

The attached archive contains the starting point for developing an OpenVG-based embedded graphics application on the Wandboard. It contains 2 items: 1) The training presentation:      These are the support slides for the OpenVG presentation held during the Linux Embedded Challenge workshop. 2) The support application:      This is a sample application meant to aid in setting up the platform for an OpenVG-based application.      In order to compile it directly on the Wandboard, you will need the arm-linux-gnueabi-g++ compiler. If it is not already installed on the board, you can obtain it by installing the g++-arm-linux-gnueabi package:      sudo apt-get install g++-arm-linux-gnueabi      Use the provided Makefile to build the application. It provides an example on how to: Set up the platform (using X11) and the EGL objects (context, rendering surface etc.) Create an OpenVG path Create a linear gradient paint Create a pattern paint based on a user-generated image Fill and stroke a path Use transformation matrices to scale, rotate and translate a rendered object  

Linux Embedded Challenge is a Linux contest for Automotive topics. Its goal is to promote Linux and Open Source software in the student world. It also targets to prove Linux can be successfully used as support for Automotive software development. Linux Embedded Challenge is aimed towards students in the terminal years from either Politechnica University of Bucharest or Military Technical Academy who have had in the past previous experience with programming on Linux.

In acest clip video va prezentam posibila schema a apartamentului , acesata schema poate suferii modificari in functie de evolutia proiectului.

Am constuit masina la care am atasat frontal camera video, sistemul de ghidare a ledurilor in functie de trafic si directia de mers, plus un controller folosit la pornirea masinii, ledurilor si dirijare. Controlul directiei de mers si al orientarii farurilor se face cu ajutorul unor servo motoare. Placuta de dezvolate este alimentata de la o baterie de 5V.

Acest videoclip este un demo al tuturor functionalitatilor pe care le-am avut de implementat in aceasta etapa.Ce am reusit sa facem: - un program de pornire a senzorului LIDAR si afisarea datelor sub forma de unghi : , distanta : - un program de client pe UDOO care trimite aceste date unui server de pe calculatorul nostru (acest lucru a fost necesar deoarece interfata grafica construita de noi nu functiona pe udoo) -o interfata grafica in OpenGL prin care toate datele primite de la client sunt afisate sub forma unor puncte dispuse circular in functie de pozitia masinii noastre (aceste puncte reprezinta obiecte din jur - masini , case , oameni ,copaci etc) -un algoritm de clustering pentru gruparea convenabila a obiectelor (cum proiectul nostru trebuie sa identifice masini, trebuie ca celelalte obiecte sa fie ignorate in reprezentarea pe harta a locurilor de parcare ocupate/vacante)

Aceasta esta macheta noastra . o sa adaugam mai multi senzori, metoda de autentificare ,leduri