I want to use the Jetson Nano to leverage any sensor readings captured by the ESP32C6 and use it for inferences downstream. In the past I would have tried to send the messages between the devices via AWS IoT Core, but over the wires using UART it is definitely much faster - single digit milliseconds over UART.
Here is the source code to use as a building block to enable a Seeed Studio XIAO ESP32C6 to send messages to a NVIDIA Jetson Nano Super over the UART protocol; uni-direction. The XIAO code is a PlatformIO project and the Jetson Nano Super is a Python script.
A Sphero RVR integrated with a Seeed Studio XIAO ESP32S3 with telemetry uploaded into, and also, basic drive remote control commands received from any where leveraging AWS IoT Core.
Lately I have been aiming to go deep on AI Robotics, and last year I have been slowly experimenting more and more with anything that is AI, IoT and Robotics related; with the intention of learning and going as wide and as deep as possible in any pillars I can think of. You can check out my blogs under the Robotics Project to see what I have been up to. This year I want to focus on enabling mobility for my experiments - as in providing wheels for solutions to move around the house, ideally autonomously; starting off with wheel based solutions bought off-shelve, followed by solutions that I build myself from open-sourced projects people have kindly contirbuted online, and then ambitiously designed, 3D Printed and built all from the ground up - perhaps in a couple of years time.
This project uses a Seeed Studio XIAO ESP32S3 microcontroller to communicate with a Sphero RVR robot via UART, while simultaneously connecting to AWS IoT Core over WiFi. The system publishes real-time sensor telemetry and accepts remote drive commands through MQTT.
The Sphero RVR uses a binary packet-based protocol over UART. Each packet contains a start-of-packet byte (0x8D), an 8-byte header with device ID and command ID, variable-length data body, checksum, and end-of-packet byte (0xD8). The RVR has two internal processors: Nordic (handles BLE, power, color detection) and ST (handles motors, IMU, encoders).
The LeRobot Follower arm is subscribed to an IoT Topic that is being published in real-time by the LeRobot Leader arm over AWS IoT Core, using a Seeed Studio XIAO ESP32C3 integrated with a Seeed Studio Bus Servo Driver Board, the driver board is controlling the 6 Feetech 3215 Servos over the UART protocol.
In this video I demonstrate how to control a set of Hugging Face SO-101 arms over AWS IoT Core, without the use of the LeRobot framework, nor using a device such as a Mac nor a device like Nvidia Jetson Orin Nano Super Developer Kit. Only using Seeed Studio XIAO ESP32C3 and AWS IoT.
