MagikEye Developer Kit enables 120 fps 3D sensing on Raspberry Pi

Raspberry Pi 3D Sensing development kit

MagikEye ILT001 developer kit (DK-ILT001) is a low-latency 3D sensing kit that connects to the Raspberry Pi’s MIPI CSI camera connector and features the company’s Invertible Light Technology (ILT) module with an infrared laser and a CMOS image sensor. The company says a “unique algorithm” developed in-house can generate 3D point cloud datasets acquired at high speeds (up to 120 fps) and with very low latency using simple hardware configuration. The kit targets researchers, students, and hobbyists working on machine vision, robotics, automated carriers, and other projects that can benefit from low-latency 3D sensing. MagikEye DK-ILT001 kit key features and specifications 850nm infrared light laser CMOS image sensor Range up to 1.5 meters (15 to 80 cm recommended) Compatibility – Raspberry Pi Zero W/3B/3B+/4 Power Supply – 3.3V (via MIPI Interface on Raspberry Pi) Power Consumption – 0.6W (average) Dimensions – 44 x 24 x 16 mm (within enclosure) Weight […]

Cynthion board enables USB Hacking through Lattice ECP5 FPGA (Crowdfunding)

LUNA USB Hacking board

Update 16/02/2023: The LUNA board has been renamed to Cynthion, but the gateware framework continues to be called LUNA. Several USB hacking/debugging boards were launched in 2020 either based on microcontrollers or FPGA with the likes of Tigard (FTDI FT2232HQ), Ollie (STM32F042), Glasgow Interface explorer (Lattice Semiconductor iCE40), or Protocol Droid (STM32). All those were launched on Crowd Supply, and there’s now another one with LUNA “multi-tool for building, analyzing, and hacking USB devices” based on a  Lattice Semiconductor LFE5U-12F ECP5 FPGA that raised over $100,000 in a few days. Cynthion hardware specifications: FPGA- Lattice Semiconductor LFE5U-12F ECP5 FPGA with 12K LUTs System Memory – 64 Mbit (8 MiB) RAM for buffering USB traffic or for user applications Storage – 32 Mbit (4 MiB) SPI  flash for PC-less FPGA configuration USB – 3x High-Speed USB interfaces, each connected to a USB3343 PHY capable of operating at up to 480 Mbps. […]

CanLite ESP32 board for CAN Bus hacking support up to two high-side switches

CANLite ESP32 CAN Bus board

Voltlog’s CanLite is not the first ESP32 CAN bus board we’ve covered here at CNX Software, having written about Olimex ESP32-EVB and CAN32 boards a few years ago. But the open-source hardware, compact CanLite board offers an alternative for CAN bus hacking with a built-in automotive-grade DC-DC converter as well as an optional two-channel high-side automotive-grade switches capable of switching up to 6A per channel. CANLite key features and specifications: Wireless module – ESP32-WROOM-32D module with Espressif ESP32-D0WD dual-core Tensilica processor, 4MB SPI flash, Wi-Fi 802.11 b/g/n up to 150 Mbps, Bluetooth 4.2 LE Terminal block for CAN Bus (ISO 11898-2 standard) up to 1Mbps via SN65HVD231 CAN transceiver. Output – High-side switching of the VBAT input up to 6A. (only if the option is purchased during checkout). Programming – 6-pin JST-SH VoltLink pin header Power Supply – 12V/0.5A via terminal block Dimensions – TBD The ESP32 CANLite board supports […]

PandaZhu – ESP32 powered 3D Printer controller board supports Marlin 2.0 & ESP3D WebUI

PandaZhu ESP32 3D Printer controller board

Around two years ago, we noted beta Marlin 2.0 support for ESP32  and some initiatives to create ESP32 powered 3D printer controller boards with built-in WiFi connectivity. Now Marlin 2.0 firmware officially supports ESP32 boards such as FYSETC E4, E4d@BOX, or MRR ESPA. Another ESP32 based 3D printer controller board has now been brought to my attention. PandaZhu supports up to eight motor drivers, up to three heaters, up to three thermistors, one external LCD display, and on the software-side, the board is compatible with Marlin 2.0 as well as ESP3D WebUI. PandaZhu board’s specifications: Wireless module – ESP32-WROOM-32 based on Espressif ESP32 dual-core Xtensa processor @ 240MHz with 520 KB SRAM, plus 4MB flash Connectivity – 802.11b/g/n up to 150 Mbps, Bluetooth 4.2 3D printer peripherals Up to 8x motor drivers Up to 3x heaters Up to 3x thermistors  with 30°C to 250°C range, BLTouch auto-leveling sensor with a […]

XUAN-Bike self-balancing, self-riding bicycle relies on flywheel, 22 TOPS Huawei Ascend A310 AI processor

XUAN-bike self-balancing self-riding bicycle

After Huawei engineer Peng Zhihui Jun fell off this bicycle, he decided he should create a self-balancing, self-riding bicycle, and ultimately this gave birth to the XUAN-Bike, with XUAN standing for eXtremely, Unnatural Auto-Navigation, and also happening to be an old Chinese name for cars. The bicycle relies on a flywheel and a control board with ESP32 and MPU6050 IMU for stabilization connected over a CAN bus to the motors, as well as Atlas 200 DK AI Developer Kit equipped with the 22 TOPS Huawei Ascend A310 AI processor consuming under 8W connected to a 3D depth camera and motor for self-riding. It’s not the first time we see this type of bicycle or even motorcycle, but the XUAN-Bike design is also fairly well-documented with the hardware design (electronics + 3D Fusion360 CAD files) and some documentation in Chinese uploaded to Github. The software part has not been released so […]

DIY Raspberry Pi 4 mini server includes UPS and OLED information display

DIY Raspberry Pi 4 mini server

While the Raspberry Pi 4 SBC has greater multimedia capabilities, it can also be used for headless projects like mini servers or networked access storage (NAS). Michael Klements’ DIY Raspberry Pi 4 mini server is especially interesting as it’s cute, and includes a UPS to handle power failures, plus an OLED display to show information. Here’s the final result. Ideally, you’d need a laser cutter and a 3D printer like the Ender 3 Pro to make the case, but most of the parts are off-the-shelf components including: A Raspberry Pi 4 SBC together with a 32GB MicroSD card for the operating system 52Pi/GeeekPi UPS Plus module (about $25) plus one or two 18650 Lithium-Ion Cells A Low Profile Ice Tower for cooling, but you could probably switch to your own (passive) cooling solution and make the device slightly more compact A 128×64 I2C OLED Display A 5V/3A Power Supply Accessories […]

DIY Linux e-Reader – postmarketOS now runs on Kobo Clara HD

Kobo Clara HD Linux postmarketOS

postmarketOS is a Linux operating system designed for phones, notably the PinePhone, and based on Alpine Linux. But now it’s possible to install the Linux distribution on Kobo Clara HD e-Reader (about $115), so you could have your own Linux e-Reader in a way that’s more versatile than with commercial solutions. The image can either be based on the vendor kernel or the mainline kernel. The latter works without modification to the X server, and the framebuffer can be used directly with either kernel, but most free e-reader programs such as koreader, plato, and inkbox are developed for the slightly different framebuffer API used in the vendor kernel. The demo below relies on Sxmo UI  optimized for the PinePhone, and Martijn Braam notes that it can be pretty hard notably because only one hardware button is present on the Kobo device while the interface requires 3 hardware input buttons. But […]

AIfES for Arduino high-efficiency AI framework for microcontrollers becomes open source

AlFes for Arduino

AIfES (AI for Embedded Systems) is a standalone, high-efficiency, AI framework, which allows the Fraunhofer Institute for Microelectronic Circuits and Systems, or Fraunhofer IMS for short, to train and run machine learning algorithms on resource-constrained microcontrollers. So far the framework was closed-source and only used internally by Fraunhofer IMS, but following a collaboration with Arduino, AIfES for Arduino is now open-source and free to use for non-commercial projects. The framework has been optimized to allow 8-bit microcontrollers such as the one found in Arduino Uno to implement an Artificial Neural Network (ANN) that can be trained in moderate time. That means offline inference and training on small self-learning battery-powered devices is possible with AIfES without relying on the cloud or other devices. The library implements Feedforward Neural Networks (FNN) that can be freely parameterized, trained, modified, or reloaded at runtime. Programmed in C language, AIfES uses only standard libraries based […]

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