https://community.element14.com/challenges-projects/project14/autohacks/ Build auto related projects such as backup assistance, back up cameras, or garage precision parking systems.en-USTelligent Community 12https://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144702Tue, 14 Dec 2021 23:53:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:7e703461-2a69-4cf0-875a-437d95f3073camgalbuhttps://community.element14.com/challenges-projects/project14/autohacks/b/blog/posts/automated-car-marshal-161218219Tue, 14 Dec 2021 11:40:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:94e29d2d-1fb9-4db7-9523-959de832ce84amgalbu1. Introduction In aeronautics, marshalling is a one-to-one visual communication and is part of aircraft ground handling, as shown in image below The idea for this project14 challenge is to build an automated marshal that will guide you while parking the car in your garage. I will use vision-based techniques to detect the plate number of the car. Then, the automated car marshal will provide visual indications to keep the car on the correct path and will warn when the stop position has been reached. The hardware components to build this project are An almighty Raspberry Pi 4 board A TFT display for Raspberry Pi: the 7" display will provide visual feedback when you are close enough to the stop position and can clearly see the display content A webcam: even if you can use a Raspicam, a USB webcam provides more freedom in terms of installation possibilities, so I choose this option A sonar: I have a MB1020 sonar module hanging around in my lab, so I decided to use this sensor to have a precise distance measure when the car is close to the stop position (less than 60 cm). When the car is farther than that, the distance is calculated from relative size of the number plate in the images captured by the webcam An Emlid Navio+ board: this was actually a later addition, along with the servos. The problem was MB1020 has inverted TTL serial signals. This means I should had to build a levels inverter circuit to connect the sonar sensor to the Raspberry Pi. However, the MB1020 also has an analog output. This brought me to the decision to use the Emlid Navio+, a very powerful (yet outdated) board designed for drone builders. two servo motors: servos was another later addition: since I am going to use the Emlid Navio+ board, and because the Emlid Navio+ board has so many PWM output channels, why not use them? Servos will mimic the gestures a marshal uses to give directions. The plan is to create an automated car marshal that can make the following signals Proceed straight Turn left Turn right Stop Here is an overview of the hardware and the connections 2. Raspberry Pi4 setup First, let's install all the software components required to build and run an Qt-based OpenCV application. I started from a fresh Raspbian Buster image (I initially tried with Bullseye, but some OpenCV dependencies are missing in the repositories for this version, so I rolled back to Buster) 2.1 Preliminary operations 2.1.1 GPU memory size The physical RAM chip is used both by the CPU and the GPU. The Raspberry Pi 4 has a 76 Mbyte GPU memory size. It can be somewhat small for vision projects, better to change this now to a 128 Mbyte. To increase the amount of memory for the GPU, use raspi-config. After this action, reboot the board 2.2.2 Update EEPRM With a fresh and clean Raspbian operating system, the last check is the EEPROM software version. I was not aware that t he Raspberry Pi 4 is partially booted from two EEPROMs (on the contrary, t he Raspberry Pi 3 had all the operating software on the SD card). These EEPROMs are programmed after PCB assembly in the factory. The Raspberry Pi foundation has recently released new and improved software for these EEPROMs. Improvements have been made, among the other things, in heat dissipation. Since machine vision applications are CPU-intensive, it's a good idea to install this update because a low CPU temperature will prolong CPU lifespan. There are more information about firmware updates here To update EEPROMs, run the following commands get the current status sudo rpi-eeprom-update update if needed sudo rpi-eeprom-update -a reboot sudo reboot 2.2.3 Increase swap size OpenCV needs a lot of memory to compile. The latest versions want to see a minimum of 6.5 GB of memory before building. On Raspberry Pi4, swap space is limited to 2048 MByte by default. To exceed this 2048 MByte limit, you will need to increase this maximum in the /sbin/dphys-swapfile sudo nano /sbin/dphys-swapfile sudo nano /etc/dphys-swapfile Reboot the board 2.1Installing Qt Raspberry PI comes with an outdated version of Qt5 (5.11). Even if there are instructions to build and install Qt5.12 LTS from source, version 5.11 is enough for my purposes so I will just install the default version sudo apt-get install qt5-default 2.2 Installing OpenCV In this github repo there is a very useful script that executes all the commands to download, build ad install OpenCV Here are the commands to run to install OpenCV 4.5.4 wget https://github.com/Qengineering/Install-OpenCV-Raspberry-Pi-32-bits/raw/main/OpenCV-4-5-4.sh sudo chmod 755 ./OpenCV-4-5-4.sh Edit the script at line 54 and change -D WITH_QT= OFF to -D WITH_QT= ON Finally run the script and wait for completion ./OpenCV-4-5-4.sh 3. Emlid Navio+ setup 3.1 Software setup Setting up software for Navio+ board is quite easy: there is a github repository with all the source code required to build a library that provides access to the board's peripherals git clone https://github.com/emlid/Navio2.git cd Navio2/C++ make In the Build folder, some example applications are built for a quick test of the hardware 3.2 Hardware setup For this project, I am going to use ADC2 channel for the sonar 2 PWM output channels for the two servo motors Even if ADC0 and ADC1 are easily available on the connector labelled "POWER", I didn't have a male connector that matched the connector on the board, so I soldered the sonar sensor wirings directly to the pads on the back of the board The two servos are connected to PWM output channels 1 and 2. Here is an overview of the hardware 4. Plate detection The initial plan was to learn something about realtime license plate recognition by leveraging some powerful technologies and tool like openalpr ssd (single shot detector) yolo (you only look once) However this solutions were really overkilled for the application I had in mind and also led to a very poor number of frames processed per second (less the 1 fps), which is obviously unacceptable if you want to provide a realtime feedback to the driver For this reason, I explored a more conventional openCV-based approach. I took inspiration for the plate detection algorithm from this project The basic steps of the algorithm are image preprocessing detect possible chars group chars and sort groups by number of chars return the most probable plate Here are some images that, better that one thousand words, explains how the processing pipeline works 4.1 Original image 4.2 Gray-scale image 4.3 Image with adaptive threshold 4.4 Contours 4.5 Contours of possible chars 4.6 Detected chars 4.7 Plate bounding rectangle 5. Application In this screenshot, information on the application user interface are shown Application logic is shown in diagram below Here are more details about the states in the flow chart above 5.1 "No car" state The application is initially in "No car" state. In this state, no plate is detected in the video stream captured by the webcam. Sonar sensor is not detecting any object as well 5.2 "Docking" state Plate detection algorithm is continuously running against the video stream from the webcam. When a plate is detected, the state is set to "Docking", meaning that a car is approaching the parking slot. In the "Docking" state, distance from stop position is calculated based on the relative size of the plate. Distance from center line is calculated based on horizontal plate position in the image. Distance is calculated according to the following formula #define PLATE_WIDTH_MM 360 #define PLATE_DISTANCE_MM 1000 #define PLATE_WIDTH_PIXELS 200 /* pixels of plate when placed at 1m */ double f = (PLATE_WIDTH_PIXELS * PLATE_DISTANCE_MM) / PLATE_WIDTH_MM; mDistanceY = (PLATE_WIDTH_MM * f) / boundingRectWidth; Distance from the center line is calculated from the horizontal distance of the plate from the center of the image. A cursor is shown on the TFT screen and the marshal "arms" are move to provide visual feedback to the driver about the corrections to make to maintain the correct direction 5.3 "Precision docking" state When the car is in the sonar detection range (about 60 cm from the stop position), application status is to "Precision docking". In this state, distance from stop position is read from sonar and is more precise than the distance calculated from relative plate size. As I already wrote, the sonar sensor is a Mobatix MB1020. This sensor as a TTL serial output the distance is transmitted on by means of simple ASCII messages. However, TTL signal is inverted (meaning that the serial "space" state is high instead of low). To connect such a sensor to the Raspberry Pi's serial would require a dedicated circuit to invert TTL signal back to standard levels. I chose for a more creative "solution": I am reading the analog output signal of the MB1020 sensor and compute distance from the voltage readouts. The signal level is somewhat erratic, so I had to implement a simple moving average algorithm to filter out peaks and show smooth distance values on the UI 5.4 " Parked " state When distance returned by the sonar drops below a given threshold, the application status is switched to "Parked" state. The TFT screen turns to red to warn the driver that the final position has been reached. Marshal "arms" are moved to a vertical position to provide a more incisive visual feedback 5.5 " Undocking " state When distance returned by the sonar increases, the application status is switched to "Undocking" state, meaning that car is leaving the parking lot. Marshal "arms" move quickly to say goodbye to the driver. Finally, when nothing is in the sonar detection range and no plate is detected, the application returns back to "No car" state 7. Construction These are some pictures I took while I was building the automated car marshal. This is made of plexiglass glued with hot glue 6. Usage The usage of the automated car marshal is very easy: you have to put the device in the position where the car is supposed to be parked. If you want to get a precise distance measurement when car is beyond sonar range, a simple calibration process needs to be followed park the car at 1 meter of distance from the automated car marshal on the UI, just above the video preview, read the width of the plate's bounding rectangle edit file mainwindow.cpp and, in the line replace the current value with the value you just read on the UI #define PLATE_WIDTH_PIXELS 200 /* pixels of plate when placed at 1m */ build and restart application 7. Demo community.element14.com/.../Docking_5F00_final.avi 8. Source code To build the application, please run the following commands git clone https://github.com/ambrogio-galbusera/docking.git cd docking qmake -r docking.pro make To run the application sudo ./docking where n is the video input device to use. To check the correct value, enter the command ls /dev/fb* You should see at least one device whose name is /dev/fb . n is the argument to add to the application command line 9. Conclusions As usual, challenges and projects on Element14 are good opportunities to think in a creative way and explore new technologies. And this project14 theme was not an exception. I discovered a lot of useful info, from some interesting details about the Raspberry Pi 4 platform to the technologies behind plate detection systems installed on our roads. The project is still in an embryonic stage. For sure, some tuning of the plate detection algorithm is required to make the calculation of the bounding rectangle less erratic. Also, sonar readouts need a better filtering algorithm to remove noise on the analog signal. Other improvements are the use of a larger HDMI monitor instead of the 7" DSI monitor and the ability to switch on and off the LED strips Hope you enjoyed this post, thanks for reading!raspberryopencvautohackschhttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144698Mon, 13 Dec 2021 05:00:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:38e0d8c7-8e16-4a5e-8d8d-21dbdbadd2bddeblinaPantomime is a configurable gesture controller unit that can be used for reliable human-machine interaction. For the demo purpose, we have shown a use case of the Pantomime in a chassis of 4WD, which here can be easily altered with a smart wheelch...https://community.element14.com/challenges-projects/project14/autohacks/b/blog/posts/pantomimeSun, 12 Dec 2021 16:00:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:f0eeb122-275c-4a43-a91d-7ffba552f080deblinahttps://youtu.be/iIlG0HFebes Inspiration Being in the field of electronic engineering, we wanted to explore and experiment with the different possibilities of working with several sensors and components. The idea of controlling mobile devices using simple hand gestures is very fascinating and useful. We also wanted to make a product that solves several problems, makes tasks easier and all-in-all be a useful tool for people. What it does Pantomime is a configurable gesture controller unit that can be used for reliable human-machine interaction. For the demo purpose, we have shown a use case of the Pantomime in a chassis of 4WD, which here can be easily altered with a smart wheelchair. The Pantomime responds to the hand gestures to control the 4wd rover. The motions we were able to show using the prototype are forward, backward, left, right. How we built it The prototype of the project was built using 4 300 RPM BO motors, 4 wheels, an L293d motor driver, a 433mHz RF (transmitter and receiver) modules to transmit and receive the gesture commands, and two Arduino Uno (one for the receiver i.e. on the rover, and the other for the transmitter circuitry) for communication and controlling purposes. Along with that, to power the rover, we used 2 3.7v Li-On batteries. The chassis was built using an acrylic board. Some basic Arduino coding was done to communicate between the transmitter and receiver with checksums. For the gesture identifying wearable, we interfaced the transmitter with a three-axis accelerometer to calculate the angle of inclination in each direction. And lastly to show the utility of the receiver we incorporated it in a 4WD rover. Challenges we ran into Setting up the transmitter and receiver modules to send and receive the gesture commands was a bit tricky, there is a lag between the gesture made and the rover to perform the respective action, but later by modifying the code with some filters and adjusting the hardware circuitry as well, we got comparatively better results. We were also having some troubles with the 5v input port of the Arduino connected to the receiver that is on the rover, but we tackled that by moving the connections to the 5v port of the ICSP headers. Accomplishments that we're proud of Completing the project on time including the PCB design, getting the prototype to work, and overcoming the obstacles faced while building it were some of our greatest achievements. What we learned We learned about RF communication and interfacing the modules with an accelerometer and a 4WD rover. We also learned about checksums, the eradication of errors, and haptic feedback. What's next for Pantomime Next, we would definitely try to make the interface much smoother and efficient. We would also like to make Pantomime market-ready and user-configurable. We are planning to test the same gesture controller on different mobile devices like drones in the future. Credits Avijit Das helped me in creating this project. Try it out GitHub Repoautohackschhttps://community.element14.com/challenges-projects/project14/autohacks/w/documents/23230/project14-auto-hacks-work-on-vehicle-projects-from-can-bus-to-camera-or-machine-vision-relatedTue, 23 Nov 2021 14:24:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:c26aa2e7-9ee9-4b05-96de-b42b5fa710fftariq.ahmadAuto Hacks Monthly Themes | Monthly Poll | Back to homepage In the Comments Below Let Us Know Auto Hacks Project Ideas! Submit Your Projects Here: Submit Entry The theme this month is Auto Hacks and it comes from a suggestion from Sean_Miller . Your project could use an IR sensor for backup assistance; involve instalingl a backup camera that allows for rotation left and right; making a garage precision parking system; involve using camera/machine vision to detect lane lines and alert on inadvertent lane change (hint, tie into the blinker circuit); or your project can involve experiments or projects related to CAN-Bus. It could also involve adding modern conveniences to a slightly older (or older) car. Check out the latest episode of element14 presents where a531016 does just that in Episode 520: Adding Android Auto as Non-Permanent Add-On with Raspberry Pi : If you have an idea for a cool auto related project share it with the community to help inspire more cool ideas that turn into finished projects on the community. Here are some projects to inspire you to come up with ideas for your project. If you have an idea for a cool auto related project let us know in the comments below. Auto Hacks Vidor4000 CAN-Bus Project by alisterw Vehicle Speed Camera - Beaglebone AI by gam3t3ch BBAI Seein' Around Corners, Talkin', IoT Exploitin' Backup Car Cam with Onboard Vision AI by Sean_Miller Driver State Monitor with OpenCV and BeagleBone AI by vlasov01 Virtual Loop Sensor by skywalker1211 A more Intelligent Idiot Light by mcb1 Building a Miniature 300W Speaker Simulator by shabaz OpenWindow: open-source car electric window controller by apreed Your Chance to Win Be Original Stick to the Theme You could come up with a clever name that make's your project memorable! This project is your baby! Part of the fun of bringing something new into the world is coming up with a name. Your project could introduce something new or that is not commercially available or affordable! If you have an idea for a project that doesn't fit the current theme then submit your idea in the comments section of the monthly poll . List the Steps Submit Video Proof Provide the steps you took to complete your project (text, video, or images). This could be a step by step how-to-guide, vlog, schematics, coding, napkin drawings, voice narration, or whatever you think will be useful! If it doesn't work that's fine, this is more about the journey than the end product. A short video is all that is required but you can shoot as much video as you like. You are encouraged to be creative and have as much fun as possible! Your Project Examples Auto Hacks Driver State Monitor with OpenCV and BeagleBone AI by vlasov01 BBAI Seein' Around Corners, Talkin', IoT Exploitin' Backup Car Cam with Onboard Vision AI by Sean_Miller : www.youtube.com/watch players.brightcove.net/.../index.html Your Prizes One Grand Prize Winner Wins a $200 Shopping Bundle Three First Place Winners Win a $100 Shopping Cart One Grand Prize Winner Wins a $200 Shopping Cart! 3 First Place Winners a Win $100 Shopping Cart! Some Terms & Conditions Apply: How to Redeem Your Shopping Cart for Project14 Your Project, Your Ideas! About Project14 Directions Every month you'll have a new poll where you'll get to decide an upcoming project competition, based on your interests, that will take place a couple of months in advance. Themes are broad in scope so that everyone can participate regardless of skill set. What are Monthly Themes? Every month (around the 14th of each month) a new theme will be posted on Project14 . Submit your ideas (proposals) for your projects to get feedback from the rest of the community. Submit a project entry in the Theme space once you start working on it. What are Monthly Theme Polls? Every month (around the 14th of each month) there is a project theme poll . Vote on which project competition you want to see for the following upcoming theme. The themes voted on during the previous poll decided the upcoming theme . If you submit an idea for a theme that is not used then it can still be used in a future poll. Themes comments and ideas from the comments section of the project theme poll . Step 1: Log in or register on element14, it's easy and free. Step 2: Post in the comments section below to begin a discussion on your idea. Videos, pictures and text are all welcomed forms of submission. Step 3: Submit a blog post of your progress on your project by the end of the month. You are free to submit as many blog entries as you like until the beginning of the next theme. Be sure to include video proof of your project! Visit: Auto Hacks or tag your project blog AutoHacksCH You have until December 14th End of Day to submit your completed project! A jury consisting of your peers will judge project submissions! In the Comments Below Let Us Know Auto Hacks Project Ideas!autohackschhttps://community.element14.com/challenges-projects/project14/autohacks/w/documentsTue, 23 Nov 2021 14:24:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:646d3f37-f381-4dcf-b99c-5c20df3868aahttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144602Mon, 22 Nov 2021 01:16:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:2caa96fd-3c00-41a9-9f7f-0cf7bec7f4f4Jan Cumpsfor this blog: https://www.element14.com/community/community/project14/autohacks/blog/2021/11/18/pi-can-node-red-and-cloudhttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144589Sun, 21 Nov 2021 06:45:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:b3d3535c-88d8-4d61-804a-2af68f74f9e1tariq.ahmadhttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144588Sun, 21 Nov 2021 06:40:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:209df2a4-ff51-4da3-a2b5-b2c5d0579119tariq.ahmadhttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144587Sun, 21 Nov 2021 06:40:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:1fcfcb4b-f184-489a-8fdf-c46262ba47dftariq.ahmadhttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144586Sun, 21 Nov 2021 06:40:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:ef18ffcb-426c-4aaa-987d-dc9cfa791d50tariq.ahmadhttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144585Sun, 21 Nov 2021 06:40:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:4e1652e8-18e3-40e3-9627-efe82121186dtariq.ahmadhttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videos/144584Sun, 21 Nov 2021 06:40:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:7677c473-7852-4e40-90d0-6b8d85072d3btariq.ahmadhttps://community.element14.com/challenges-projects/project14/autohacks/m/managed-videosSun, 21 Nov 2021 06:40:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:9bd6770c-f54c-414e-9f5f-ddfcae4a6d69https://community.element14.com/challenges-projects/project14/autohacks/w/setup/26713/featured-video-setup-docSun, 21 Nov 2021 06:35:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:0b0b7943-5ca3-4ec3-b6e4-17e85bd7bfcatariq.ahmadcommunity.element14.com/.../Jan-The-Van-Part-1-_2D00_-01_5F00_V1_2D00_0001.mp4 community.element14.com/.../Jan-The-Van-Part-1-_2D00_-01_5F00_V1_2D00_0002.mp4 community.element14.com/.../Jan-The-Van-Part-1-_2D00_-01_5F00_V1_2D00_0003.mp4 community.element14.com/.../Jan-The-Van-Part-1-_2D00_-01_5F00_V1_2D00_0004.mp4 community.element14.com/.../Jan-The-Van-Part-1-_2D00_-01_5F00_V1_2D00_0005.mp4 community.element14.com/.../Jan-The-Van-Part-1-_2D00_-01_5F00_V1_2D00_0006.mp4featuredVideohttps://community.element14.com/challenges-projects/project14/autohacks/w/setupSun, 21 Nov 2021 06:35:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:369f64f4-9ff1-4fb4-ae98-5f6143dd9a3ahttps://community.element14.com/challenges-projects/project14/autohacks/w/setup/26714/featured-projectsSun, 21 Nov 2021 06:16:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:7eca0d54-dd9f-45c9-8229-11ee41cab8e1tariq.ahmadEnable Raspberry Pi CAN with an Arduino Shield Adding Android Auto as Non-Permanent Add-On with Raspberry Pi OpenWindow: open-source car electric window controller Vidor4000 CAN-Bus Project Vehicle Speed Camera - Beaglebone AI BBAI Seein' Around Corners, Talkin', IoT Exploitin' Backup Car Cam with Onboard Vision AIhttps://community.element14.com/challenges-projects/project14/autohacks/b/blog/posts/enable-raspberry-pi-can-with-an-arduino-shieldThu, 18 Nov 2021 14:06:00 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:a2dcda45-a4fd-49b2-8d4e-789b41f6085bJan CumpsAn out-of-box Pi doesn't have CAN support. This Project14 mini-project shows how you can give it a CAN bus with an Arduino CAN Shield Arduino CAN Shield . The end result is a Pi with a physical CAN driver and the Linux CAN-utils software installed and ready to use. Craig Peacock wrote the instructions to integrate several CAN breakout boards with the Pi . I'm adding the Arduino MKR CAN Shield to that. In the spirit of Project14, it's a very simple project. If you happen to own a CAN shield, you can play along. Connections All signals and voltages are available on the Pi's 40-pin connector. The table below cross-references all required signals, the location on the Pi header and the Shield pin . I used the same Pi pins as Craig. click to enlarge Warning : https://forum.arduino.cc/t/wiring-a-mkr-canbus-shield-to-an-arduino-uno/670010 Also beware that the MKR Canbus Shield has an error on labeling the Can H and Can L on the BOTTOM of the board. They are reversed. They are correct on the top of the board (in micro letters). If the Shield is an end node (first or last unit connected to your CAN bus), set the terminate switch on the shield towards the resistor symbol. Linux CAN-utils Tools I literally followed the steps of Craig's post . Do the same. Follow the Driver Installation and CAN-util sections . (not needed, because the overlay does it automatically: But first enable SPI interface with raspi-config). I used a fresh Debian Buster Lite. First enabled the driver for the MicroChip CAN controller by enabling an overlay. Attention. The Arduino Shield has a 16 MHz crystal, so the oscillator attribute in the overlay string should be set to 16000000: dtoverlay=mcp2515-can0,oscillator=16000000,interrupt=25 I tested if that was successful. dmesg reports a successful load: Then I installed the CAN-utils package (check Craig's post for instructions). I'm using the cansend and candump utilities of that package. www.youtube.com/watch action video: hardware setup (with audio) Testing It I used a MicroChip CAN Bus analyser (see links at the end of this project). Ground, CAN Hi and CAN Lo of analyser and Shield are connected to each other (attention: wrongly labeled on the underside of the Shield). Can Hi and CAN Lo wires should be twisted. I then used both devices to exchange data and show the results. In both directions Success! www.youtube.com/watch action video: it works (no audio) Related Blog: Test CAN BUS on BeagleBone Arduino MKR CAN Shield Review - part 1: Log BUS Traffic Arduino MKR CAN Shield Review - part 2: Interrupt and Filter AVNET SmartEdge IIOT Gateway: Use the Isolated CAN CAN programming in C on Linux: Filter and Mask CAN Analyser Road Test Microchip CAN Analyzer Road Test - part 1: First trials Microchip CAN Analyzer Road Test - part 2: Inject CAN Messages Microchip CAN Analyzer Road Test - part 3: Analyzer as Test Tool Microchip CAN Analyzer Road Test - part 4: Analyze the Physical layer of CAN Bus Microchip CAN Bus Analyser Tool - Review Poor man's CAN: TI Hercules LaunchPad - test the CAN with a poor man's CAN driver Probing your Hercules LaunchPad CAN bus Part 1 Probing your Hercules LaunchPad CAN bus Part 2 Probing your Hercules LaunchPad CAN bus Part 3 Make my own CAN Driver: CAN communication with Hercules Safety Microcontroller - part 1: tryout CAN communication with Hercules Safety Microcontroller - part 2: Communication between 2 Devices CAN communication with Hercules Safety Microcontroller - part 3a: Design a Bus Driver PCB CAN communication with Hercules Safety Microcontroller - part 3b: Design a Bus Driver PCB - Schematics and Custom Components CAN communication with Hercules Safety Microcontroller - part 3c: Design a Bus Driver PCB - Layout CAN communication with Hercules Safety Microcontroller - part 3d: Design a Bus Driver PCB - Testautohackschcan_bus