The Waveshare UGV Rover is a 6-wheel robot platform based on Raspberry Pi 4 or 5 as well as an ESP32 module and built for remote exploration, object recognition, and autonomous navigation. Since the source code for the platform will be open-sourced it can also be used for educational purposes, programming, robotics, AI experimentation, and many other applications. This Unmanned Ground Vehicle (UGV) rover features a 2mm thick aluminum body, six 80mm shock-absorbing tires, and a four-wheel drive system controlled by an ESP32 sub-controller. The sub-controller also handles sensors, LiDAR, cameras, and more. The brain or the main controller of the rover is a Raspberry Pi SBC – either a Pi 4B or Pi 5 – which notably handles computer vision and machine learning operations. Since the mounting holes are designed to fit a Raspberry Pi, it is safe to assume that it will fit other SBCs with the same […]
QNAP TS-216G 2-bay NAS features a quad-core Arm processor with NPU for image sorting and searching
QNAP TS-216G 2-bay NAS features a quad-core Arm Cortex-A55 processor with an NPU for AI-powered photo management, 4GB RAM, 2.5GbE and GbE networking ports, two hot-swappable 3.5-inch SATA bay, and a few USB ports. It looks to be an update to the Rockchip RK3566-powered QNAP TS-133/TS-223 with more memory (4GB vs 2GB) and more advanced networking capability (2.5GbE+GbE vs GbE only), while still keeping the object and face recognition capabilities. QNAP TS-216G specifications: SoC – Unnamed but likely Rockchip RK3566 CPU – Quad-core Cortex-A55 clocked at up to 2.0 GHz GPU – Mali-G52 Neural Processing Unit (NPU) Hardware-accelerated Transcoding Encryption Engine System Memory – 4 GB RAM Storage 4 GB eMMC flash (dual boot OS protection) 2x 3.5-inch SATA III bay also supporting 2.5-inch SATA SSDs; hot-swappable Networking 2.5GbE RJ45 jack Gigabit Ethernet jack Wake-on-LAN (WoL) and Jumbo Frame support Number of Concurrent Connections (CIFS) – Up to 200 USB […]
Pivistation 5 – A Raspberry Pi 5 Camera Kit to quickly get started with computer vision (Crowdfunding)
Arducam Pivistation 5 is an all-in-one Raspberry Pi 5 camera kit that aims to provide a turnkey hardware and software solution to quickly get started with computer vision applications and offered with a choice of camera sensors designed for various applications. The system looks like a Raspberry Pi 5 SBC housed in the official case fitted with a camera. Three models are available, namely the “Hawkeye” featuring a high-resolution 64MP autofocus camera, the “Darksee” with an 8MP camera sensor with ultra low-light sensitivity, and the “Klarity” with a 20MP camera with fixed focus and a large 1-inch sensor. Pivistation 5 specifications All the cameras above rely on a rolling shutter, but the company is also working on the upcoming Arducam Pivistation 5 Swift model that includes a global shutter for robotics applications. Besides the pre-assembled hardware, the Arducam Pivistation 5 family aims to quicken the development process with pre-installed software […]
Qualcomm RB3 Gen 2 Platform with Qualcomm QCS6490 AI SoC targets robotics, IoT and embedded applications
Qualcomm had two main announcements at Embedded World 2024: the ultra-low-power Qualcomm QCC730 WiFi microcontroller for battery-powered IoT devices and the Qualcomm RB3 Gen 2 Platform hardware and software solution designed for IoT and embedded applications based on the Qualcomm QCS6490 processor that we’re going to cover today. The kit is comprised of a QCS6490 octa-core Cortex-A78/A55 system-on-module with 12 TOPS of AI performance, 6GB RAM, and 128GB UFS flash connected to the 96Boards-compliant Qualcomm RBx development mainboard through interposer, as well as optional cameras, microphone array, and sensors. Qualcomm QCS6490/QCM6490 IoT processor Specifications: CPU – Octa-core Kryo 670 with 1x Gold Plus core (Cortex-A78) @ 2.7 GHz, 3x Gold cores (Cortex-A78) @ 2.4 GHz, 4x Silver cores (Cortex-A55) @ up to 1.9 GHz GPU – Adreno 643L GPU @ 812 MHz with support for Open GL ES 3.2, Open CL 2.0, Vulkan 1.x, DX FL 12 DSP – Hexagon […]
Axelera Metis PCIe Arm AI evaluation kit combines Firefly ITX-3588J mini-ITX motherboard with 214 TOPS Metis AIPU PCIe card
Axelera has announced the general availability of several Metis PCIe AI Evaluation Kits that combine the company’s 214 TOPS Metis AIPU PCIe card with x86 platforms such as Dell 3460XE workstation and Lenovo ThinkStation P360 Ultra computers, Advantech MIC-770v3 or ARC-3534 industrial PCs, or the Firefly ITX-3588J mini-ITX motherboard powered by a Rockchip RK3588 octa-core Cortex-A76/A55 SoC. We’ll look into detail about the latter in this post. When Axelera introduced the Metis Axelera M.2 AI accelerator module in January 2023 I was both impressed and doubtful of the performance claims of the company since packing a 214 TOPS Metis AIPU in a power-limited M.2 module seemed like a challenge. But it was hard to check independently since the devkits were not available yet although the company only started their early-access program in August last year. Now, anybody with an 899 Euros and up budget can try out their larger Metis […]
Digi ConnectCore MP25 SoM targets Edge AI and computer vision applications with STM32MP25 MPU
Digi International has announced its latest system-on-module (SoM), the Digi ConnectCore MP25 SoM, based on STM32MP25 MPU at Embedded World 2024 in Nuremberg, Germany. The Digi ConnectCore MP25 SoM is built upon STMicroelectronics’ STM32MP25 microprocessor. It supports artificial intelligence and machine learning functionality through an integrated neural processing unit (NPU) capable of 1.35 tera operations per second (TOPS) and an image signal processor (ISP). It is powered by two 64-bit Arm Cortex-A35 cores running at 1.5GHz, supported by a 32-bit Cortex-M33 core operating at 400MHz and a 32-bit Cortex-M0+core running at 200MHz. With its machine learning capabilities, support for time-sensitive networking, and versatile connectivity features, the ConnectCore MP25 module is suitable for edge AI, computer vision, and smart manufacturing applications in various sectors, including medical, energy, and transportation. Digi ConnectCore MP25 specifications: SoC – STMicroelectronics STM32MP257F CPU – 2x 64-bit Arm Cortex-A35 @ 1.5 GHz; MCU 1x Cortex-M33 @ 400 […]
Toradex Aquila AM69 SoM features TI AM69A octa-core Cortex-A72 AI SoC, rugged 400 pin board-to-board connector
Toradex Aquila AM69 is the first system-on-module (SoM) from the company’s Aquila family with a small form factor and a rugged ~400-pin board-to-board connector targetting demanding edge AI applications in medical, industrial, and robotics fields with Arm platforms that deliver x86 level of performance at low power. The Aquila AM69 SoM is powered by a Texas Instruments AM69A octa-core Arm Cortex-A72 SoC with four accelerators delivering 32 TOPS of AI performance, up to 32GB LPDDR4, 128GB eMMC flash, built-in WiFi 6E and Bluetooth 5.3 module, and a board-to-board connector for display, camera, and audio interfaces, as well as dual gigabit Ethernet, multiple PCIe Gen3 and SerDes interfaces. All that in a form factor that’s only slightly bigger (86x60mm) than a business card or a Raspberry Pi 5. Toradex Aquila AM69 specifications: SoC – Texas Instruments AM69A Application processor – Up to 8x Arm Cortex-A72 cores at up to 2.0 GHz […]
AMD Ryzen Embedded 8000 Series processors target industrial AI with 16 TOPS NPU
AMD has recently “announced” the Ryzen Embedded 8000 Series processors in a community post with the latest AMD embedded devices combining a 16 TOPS NPU based on the AMD XDNA architecture with CPU and GPU elements for a total of 39 TOPS designed for industrial artificial intelligence. The Ryzen Embedded 8000 CPUs will be found in machine vision, robotics, and industrial automation applications to enhance the quality control and inspection processes, enable real-time, route-planning decisions on-device for minimal latency, and predictive maintenance, and autonomous control of industrial processes. AMD Ryzen Embedded 8000 key features and shared specifications: CPU – Up to 8 “Zen 4” cores, 16 threads Cache L1 Instruction Cache – 32 KB, L1 Data Cache = 32 KB (per core) L2 Cache – Up to 8 MB (total) L3 Cache-Â Up to 16 MB unified Graphics – RDNA 3 graphics with up to 6 WGPs (Work Group processors) […]