Monthly Archives: December 2021

Quite easy. Follow the following installation guide here. Note: Choose the right processor architecture from here https://github.com/zephyrproject-rtos/sdk-ng/releases  Run the “Hello World” example as described here.

Cool video on Zephyr OS project:

The “V” has two sides; on left down and on right up. On left: Requirements System design Architecture design Module design Coding On right: Coding Unit testing Integration testing System testing Acceptance testing V&V is in the following relationship: The … Continue reading →

While diving through Google for AUTOSAR classic I found openOSEK.org as the automotive real-time operating system (RTOS). OSEK is a/the  ISO17356 Standard implementation. Under the section “Why OSEK” the following sentences confused me: Most of these alternatives are quite bulky … Continue reading →

Flexible deployment via type 1 or type 2 hypervisor Description of resources via key value sets (Distributed) resource (-state) management   (Multiple) (autonomous) software agent node’s  Data passing between computational nodes  Task passing between computational nodes Functional and semantically agreed … Continue reading →

So many options today… Let us start on high level. We have to distinguish container hypervisor versus virtual machine hypervisor. Container hypervisor can be separated into application container e.g., Docker (runc with lib container as reference runtime from OCI, implemented … Continue reading →

Based on ROS2 libraries (feature comparison) the microROS is constructed. It is made for microcontroller devices with small main memory and processors. Programs written via microROS can be hosted from bare-metal through RTOS (e.g., NuttX, FreeRTOS, VxWorks) to GPOS (e.g., … Continue reading →

Due to https://www.adlinktech.com/en/soafee the following building blocks would be applied Open Robotics ROS 2 with Autoware.Auto Eclipse Cyclone DDS iceoryx zero-copy Zenoh V2X

CNN does support an extensive amount of use cases, not only computer vision one. Nevertheless, it underperforms with variations e.g. rotations. The convolutional layers in front of the fully connected layer act as filter, as dot-product with a field e.g., … Continue reading →

The main differences are: Management of filesystem: Docker manage the filesystem multi-layered, LXC only knows a directory hosting the root filesystem. Client tools: Docker focuses on developer and LXC on system-administrator. Image distribution: Docker has private and public registries. LXC … Continue reading →