ESP32 Teaching Lab Kit
A teaching lab kit made in Taiwan. One kit covers many needs, so you do not have to piece parts together from different sources.
Covers Robot Operating System (ROS), edge computing, and computer vision, suited to lab courses, research projects, and industry-academia collaboration.
Kits
Each card shows class periods and curriculum links.
A teaching lab kit made in Taiwan. One kit covers many needs, so you do not have to piece parts together from different sources.
The Heart Rate and Blood Oxygen Sensor Kit pairs a TTGO T-Display ESP32 board with a MAX30100 sensor module, so students can build a wearable heart rate and blood oxygen measuring device by hand.
An IoT cabin teaching kit that uses the LinkIt 7697 as its main board. Students learn how to write programs and use sensors, and combine them with web services to explore the Internet of Things.
JetBot is an open-source AI robot platform that NVIDIA built on its own AI development kit, the Jetson Nano.
Pixel:Bit combines dual ESP32 and ATmega328P controllers with a 5-megapixel camera module, and can be used for edge computing projects such as video streaming, face recognition, and TinyML image recognition.
The ROSKY Smart Mobile Platform features an NVIDIA Jetson Nano, a LiDAR sensor, and a wide-angle camera. Through the ROS course, students learn remote control, SLAM mapping, and navigation, and build robotics projects such as the Timed Rescue Challenge.
The ROSKY2 Smart Mobile Platform uses an NVIDIA Jetson Nano with a LiDAR sensor and a vision camera. Through the ROS 2 course, students learn core robot operating system concepts such as nodes, publish/subscribe, and services, and build mobile robot projects such as wall following.
An autonomous mobile robot built on Raspberry Pi 4 and ROS 2 Humble. It maps the maze with LiDAR, then navigates freely with no guide lines or tracks. The operating system and control software come pre-installed, so it is ready to use out of the box.
Build an Industry 4.0 smart factory model by combining Internet of Things (IoT) big data collection with robotics and machine vision.
Build an AIoT smart home system using IoT data collection, cloud big data, and AI applications.
A ROS 2 robot built on a single-board computer and a three-axis omnidirectional wheel platform, with LiDAR and a camera for real-time mapping, map navigation, and computer vision.
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