Nvidia Jetson Research Page
Yup. Title. I’m gonna have to learn how to use confluence.
Communication with Jetson vs SPI/CAN/ETC/WHATEVER WE WANT
needs much more research.
need to confirm what data is being transferred. Is the camera module being handled by the jetson entirely? are we just getting position from cv? what’s the plan……
There is a tool called Jetson_IO that can be used to make configuring GPIO pins easier.
The jetson nano has two headers used for communication, the J41 and J44. J44 is referred to as the Serial Port Header, and J41 is referred to as the GPIO header. Look here for J41 pinout: https://www.jetsonhacks.com/nvidia-jetson-nano-j41-header-pinout/ .
I/O | Notes |
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I2C |
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UART |
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I2S |
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USB? |
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RTOS (zp) on Jetson?
Concurrent Redhawk Linux is supported on Jetson TX1/TX2, Nano, and Jetson AGX Xavier. This is an RTOS version of Linux.
Seems like there is already a FreeRTOS too.
zephyr doesn't seem to have any board support for ARM Cortex-A57, or Carmel ARMv8.2.
CV on RTOS?
might have issues ← come back to this.
RPi vs Jetson
Below we find our comparisons between our different device considerations. These are the specs for the device module, not the developer kit.
Benchmark | RPI | Jetson Nano | Jetson Xavier | JEtson TX2 |
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Physical specifications | RPI (RPI4 Model B ) | |||
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Power consumption | Can range between 2.56W to 7.30W | Between 5W to 10W | Between 10W to 30W | Between 7.5W to 15W |
CPU |
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RAM (volatile memory) and Memory storage |
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GPU |
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Has tensor cores (64) |
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Networking and Display (USB, ethernet, etc.) |
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Supported communication interfaces | GPIOs | Supports GPIO, I2C, I2S, SPI, UART | Supports UART, SPI, CAN, I2C, I2S, DMIC & DSPK, GPIOs | Supports GPIOs, I2C, I2S, SPI, CAN, and TTL UART with flow control |
Cost | Starting from $35 (increases depending on RAM) | $149 | $999 | Starting at $299 Jetson TX2 NX is $199 but is smaller and has less RAM. |
Notes:
Between RPI4 and Jetson Nano, RPI4 is slightly better in terms of Display and CPU. RPI also has built-in wifi (which is nice). The general computing performance between both devices is relatively similar; however, when it comes to machine learning, 3D graphics, or very complex algorithms, Jetson Nano is better thanks to its GPU.