SPECIFICATIONS

Application_1: Programmable Robot

Application_2: Smart Car

Application_3: Educational Robot

Application_4: DIY Projects

Application_5: ROS ROBOT

Brand Name: YAHBOOM

CPU: 6 cores Arm Cortex-A78AE v8.2 64bit CPU 1.5MB L2 +4MB L3

Camera: CSl Port *2

Display: DP

Features_1: Artificial Intelligence

Features_2: Image Processing

Features_3: Embedded development platform

Features_4: Pytho Programming

Features_5: Programmable Toys

Features_6: HighTech Toys

Features_7: AI Large Model

High-concerned chemical: None

Is Electric: No Battery

Model Number: Jetson Orin NANO

Origin: Mainland China

RAM: 4GB/8GB

Recommend Age: 14+y

Size of Jetson Orin NANO board: 90*93mm

Storage: 256G SSD for free

USB Port: 4*USB3.0(22PIN)

Version: Jetson Orin NANO SUPER

Jetson Orin NANO SUPER Developer Kit Based on Official Core Module Embedded Development Board for Python ROS AI Deep Learning

100% brand new and high quality

Description:
The Jetson Orin Nano SUPER developer kit consists of NVIDIA's Jetson Orin Nano core module and the Jetson Orin Nano carrier board. 4G/8GBRAM available. Computing power of 4G board can reach 34 TOPS, computing power of 8G board can reach 67 TOPS. The performance, on board resources, size, and interface layout of the Yahboom carrier board are consistent with the official NVIDIA carrier board. 256GB M.2 SSD that has been written into the system, WiFi network card and antenna, power supply will be provided for free.

1.Yahboom carrier board is perfectly compatible with Nvidia's Jetson Orin Nano core module. Exquisite workmanship, stable power supply.

2.The kit includes a 256GB M.2 SSD solid-state drive, a WiFi network card, two antennas, and a power adapter.

3.Compared with the entry-level Jetson Nano B01, Jetson Orin Nano interface resources are optimized and upgraded, and the performance is improved. It is more suitable for users who need to learn artificial intelligence in depth or create difficult projects.

4.Based on the Ubuntu 20.04 system, Yahboom provides a large number of tutorials and open source codes related to ROS and AI vision.