A Closer Look at NVIDIA Jetson Xavier Developer Kit (Video)

NVIDIA Jetson Xavier Developer Kit

NVIDIA unveiled Jetson Xavier module and devkit last month, but the company did not release the full information, and for example we did not get any clear photo of the module and kit. Charbax did shot a video with more details at the time, but NVIDIA has now published more information about their upcoming $1,299 Jetson Xavier Developer Kit, including an introduction video which I’ll  embed at the end of this article. The first thing to understand is that the module is not actually used in the developer kit, and will only used in actual mass-produced products. The main  difference is the thermal solition. The development kit including a large heatsink, while the production module has a thermally conductive plate to let product designer select the most suitable thermal solution for their products. The specifications are still basically the same. For Jetson Xavier (production) module: SoC – NVIDIA Jetson Xavier with 8x 64-bit Armv8.2 processor with 8MB L2 cache and …

NVIDIA Introduces Jetson Xavier Devkit and Isaac Robotics Software

NVIDIA Jetson Xavier

NVIDIA Xavier was first unveiled in September 2016 as an artificial intelligence SoC with eight NVIDIA Custom 64-bit Arm cores, a 512-core Volta GPU,  8K video encoding and decoding, and a computer vision accelerator (CVA) now called NVDLA (NVIDIA Deep Learning Accelerator). Earlier this year, the company announced Xavier was sampling,  and DRIVE IX & DRIVE AR SDKs for the automotive market. On the eve of Computer 2018, NVIDIA has introduced Jetson Xavier development kit, as well as Isaac robotics software for autonomous machines. Jetson Xavier key specifications: SoC – NVIDIA Xavier with 8-core ARMv8.2 64-bit CPU, 8MB L2 + 4MB L3 512-core Volta GPU with Tensor Cores 2x NVDLA engines for deep learning 7-way VLIW Processor for vision acceleration VPU with dual 4Kp60 video decoding and encoding System Memory – 16GB 256-bit LPDDR4x | 137 GB/s Storage – 32GB eMMC 5.1 flash Display – 3x eDP/DP/HDMI at 4Kp60 | HDMI 2.0, DP HBR3 Camera 16x CSI-2 Lanes (40 Gbps …

A 6-Part BeagleBone Webinar for Users, Developers and Education Starts on May 10

BeagleBone-Webinar

The BeagleBone Black and derivatives like PocketBeagle or BeagleBone Green Wireless are still popular development boards, and if you are interested in the platform as a developer, user, or educator, you may learn more about the boards and how to use them in an upcoming BeagleBone webinar series presented by Jason Kridner, the co-founder and board member at BeagleBoard.org Foundation,  and element14. The webinar series will start in about 2 weeks with the following schedule: Introduction to BeagleBone –  10th May 2018 @ 11:00 AM (CDT)/17:00 (GMT) BeagleBone for Linux Users – 24th May 2018 @ 11:00 AM (CDT)/17:00 (GMT) BeagleBone for Embedded Developers – 6th June 2018 @ 11:00 AM (CDT)/17:00 (GMT) BeagleBone for Web Developers – 21th June  2018  @ 11:00 AM (CDT)/17:00 (GMT) BeagleBone Blue for Robotics – 12th July 2018 @ 11:00 AM (CDT)/17:00 (GMT) BeagleBone in the Classroom – 26th July 2018  @ 11:00 AM (CDT)/17:00 (GMT) I understand attending the webinar is free, and …

Qualcomm QCS603 / QCS605 “IoT” SoCs are Designed for AI and Computer Vision Applications

Qualcommn has unveiled the “Qualcomm Vision Intelligence Platform”, which aims at IoT devices with camera leveraging artificial intelligence and computer vision. The first SoCs part of the platform are QCS605 and QCS603 manufactured with a 10nm process, and equipped with an “advanced image signal processor” and the Qualcomm Artificial Intelligence (AI) Engine, as well Arm CPU cluster, Adreno GPU, and Hexagon DSP. QCS603 & QCS605 specifications: CPU QCS603 – 2x 1.6GHz Qualcomm Kryo 300 Gold cores, 6x 1.7GHz Qualcomm Kryo 300 Silver cores QCS605 – 2x 2.5GHz Qualcomm Kryo 300 Gold cores, 6x 1.7GHz Qualcomm Kryo 300 Silver cores Qualcomm Artificial Intelligence Engine DSP Qualcomm Hexagon 685 Vector Processor 2x Qualcomm Hexagon Vector eXtensions (HVX) GPU – Qualcomm Adreno 615 with OpenGL ES 3.2, Vulkan, OpenCL support Neural Processing – Qualcomm Snapdragon Neural Processing Engine programming interface with support for Tensorflow, Caffe/Caffe2, ONNE, Android NN; 2.1 TOPS @ 1w Memory I/F – 16-bit LPDDR4x @ up to 1866MHz Connectivity WiFi …

Getting Started with TinyLIDAR Time-of-Flight Sensor on Arduino and Raspberry Pi

TinyLIDAR is an inexpensive and compact board based on STMicro VL53L0X Time-of-Flight (ToF) ranging sensor that allows you to measure distance up to 2 meters using infrared signals, and with up to 60 Hz. Contrary to most other VL53L0X boards, it also includes an STM32L0 micro-controller that takes care of most of the processing, frees up resource on your host board (e.g. Arduino UNO), and should be easier to control thanks to I2C commands. The project was successfully funded on Indiegogo by close to 600 backers, and the company contacted me to provided a sample of the board, which I have now received, and tested with Arduino (Leonardo), and Raspberry Pi (2). TinyLIDAR Unboxing I was expecting a single board, but instead I received a bubble envelop with five small zipped packages. Opening them up  revealed three TinyLIDAR boards, the corresponding Grove to jumper cables, and a bracket PCB for three TinyLIDAR boards together with headers and screws. So I …

Pulurobot is a Low Cost Open Source Raspberry Pi based Load Carrying Autonomous Robot

Earlier today I wrote about FOSDEM 2018 schedule, and among the various talks I selected for my virtual schedule was “How to build an autonomous robot for less than 2K€”.  Some excerpt from the abstract including a short description of the project, and its “open-sourceness”: PULUrobot solves the autonomous mobile robotics complexity issue without expensive parts, without compromise. By fearless integration and from-scratch design, our platform can do SLAM, avoid obstacles, feed itself, and carry payload over 100kg, for less than 2,000 EUR. Application ecosystem can be born around it, as we offer a ready-made Open Source (GPLv2) solution in a tightly coupled HW-SW codesign. So I decided to have a closer at this project, which can be used as a robot maid/helper of sort, and other applications. The robot was made by a brand new (July 2017) startup called Pulu Robotics Oy and based in Finland. They have three models: Pulurobot S – Small version capable of carrying up …

FOSDEM 2018 Open Source Developers Meeting Schedule

FOSDEM (Free and Open Source Software Developers’ European Meeting) occurs every year on the first week-end of February, where developers meet for two days discussing about open source software projects. FOSDEM 2018 will take place on February 3-4 this year with  652 speakers, 684 events, and 57 tracks, an increase over  last year 608 speakers, 653 events, and 54 tracks. There will be 8 main tracks namely: Community, History, Miscellaneous, Performance, Python, Security and Encryption, Space, and Global Diversity CFP Day. There will also be 33 developer rooms, and since the full schedule is now available, I’ll make a virtual schedule mostly based on sessions from the Embedded, mobile, and automotive, Hardware Enablement, and Internet of Things devrooms. Saturday 3, 2018 09:50 – 10:15 – Turning On the Lights with Home Assistant and MQTT by Leon Anavi In this presentation you will learn the exact steps for using MQTT JSON Light component of the open source home automation platform Home …

Quokka IoT FPGA Board is Programmable with C# Language (Crowdfunding)

Quokka FPGA IoT Controller is a board based on Altera Cyclone IV FPGA with a WiPy module for connectivity, and various I/Os that allows you to make robotics projects for example. While you could program the FPGA using VHDL, the developer – Evgeny Muryshkin – also designed Quokka Development Toolkit (QDT), a cloud-based SaaS, allowing to program FPGA with a high-level programming language, currently C#, so that software people can more easily become involved in FPGA development. Quokka IoT (preliminary) hardware specifications: FPGA – Intel Altera Cyclone IV, 6K logic elements, EP4CE6E22C8 Clock – 50MHz Connectivity – WiFi via WiPy module Expansion 40x GPIO (3 banks by 8 pins, with direction and voltage (3.3V or 5V) configuration, 16 raw IO pins 3.3V) 2x Dual Channel 10 bit ADC (3.3V) 2x Dual Channel 10 bit DAC (3.3V) H-Bridge for DC motors with support for external power Power Supply – 5-24V DC input The specifications are preliminary, because the FPGA may be replaced …