Description
The AGX302 Rogue-T5 is a full featured NVIDIA® Jetson Thor™ module carrier board. This carrier board is specifically designed for commercially deployable platforms and has a small footprint of 92mm x 108mm.
Rogue-T5 provides access to an impressive list of latest generation interfaces on the NVIDIA® Jetson Thor™. See the table below for a full list of product features.
Rogue-T5 has been designed to be compatible with camera add-on expansion boards such as the GMSL3, GMSL2, 3G-SDI Vision Platform and more to interface directly with NVIDIA® Jetson Thor™ high density MIPI CSI interfaces.
FEATURES
- NVIDIA Jetson AGX Thor embedded
- NVIDIA 699 pin B2B Connector
- 2x M.2 2280 M-Key NVMe for storage
- 1x M.2 2230 E-Key with PCIe and USB for expansion
- 1x M.2 3042/3052 B-Key with SIM, USB3 for LTE/5G expansion
- 2x 10GBASE-T LAN IX Industrial Rugged (10G Ethernet)
- 1x 2.5GBASE-T LAN IX Industrial Rugged (2.5G Ethernet)
- 1x USB 3.2 Samtec ARF6 Locking, 1x USB 3.2 Type-C OTG Capable, 2x UART, USB Debug UART, 4x CAN 2.0b Ports
- 1x Display port output 4x 2160@60Hz
- 1x 16-lane MIPI Expansion connector (for MIPI CSI, GMSL2 or FPD-Link III image sensors)
- Linux OS with BSP (board support package)
- Supports deep learning trained models
- This AI ready Carrier board brings the processing abilities to launch the next generation of AI systems
Purpose-built for the NVIDIA® Jetson Thor™, Rogue-T5 Carrier Board delivers industrial-grade performance, ultra-fast networking, and advanced sensor integration—engineered to accelerate the next generation of physical AI, robotics, autonomy, and AI at the edge.
With a comprehensive suite of interfaces and expansion options, Rogue-T5 unlocks the performance of NVIDIA’s Blackwell GPU.
Built for high-performance edge AI, it enables advanced robotics, autonomous vehicles, and perception systems with support for high-speed networking, NVMe storage, and secure, locking connectors for I/O.
This approach allows clients to develop a product using a commercial off the shelf (COTS) system development/baseboard/carrier board for the proof of concept or production units. If the product or project has specific dimensional, I/O or connector placement requirements a custom carrier board can be created in as little as a month. Use of an off-the-shelf carrier board allows clients to start developing their software while the custom carrier board is being designed and build. Using the SoM approach, product lifecycle concerns for the processor, memory and other SoM based components are minimized.
Bring your next-gen products to life with the world’s most powerful AI computers for energy-efficient autonomous machines. NVIDIA® Jetson Orin™ modules give you up to 275 trillion operations per second (TOPS) and 8X the performance of the last generation for multiple concurrent AI inference pipelines, plus high-speed interface support for multiple sensors. With seven different modules based on the same architecture–from the entry-level Jetson Orin Nano™ to the highest performance Jetson AGX Orin™– this is the ideal family for a new age of robotics.
The System On Module approach provides the flexibility of a fully customized product at a greatly reduced cost.
EMAC is a global leader in system on module and carrier board embedded systems. The System on Module (SoM) is an ideal alternative to custom engineering. With the SoM approach you get the best of aspects of both buying an Off-The-Shelf Embedded Single Board Computer (SBC) and a Custom Engineered solution. With Off-The-Shelf embedded components such as a generic carrier board and SOM module, it is possible to start development on your software applications before the custom carrier board is complete; thus offering a reduced time to market for your system. A System on Module (SoM) is comprised of a small processor module with CPU bus accessibility and standard I/O functionality. The SoM module does not have any connectorization and is designed to be plugged into a Carrier Board.
Need a Custom Carrier board Based on an Nvidia Jetson AGX Orin Module, Learn More Here
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