Embarking on the journey of training a pallet model requires meticulous preparation of the dataset. In this guide, we’ll walk through the crucial steps from collecting images to organizing data for effective training. Let’s dive in! Collecting Images for Training Before you begin training your pallet model, assemble a dataset of images relevant to your objectives. The size of the dataset depends on the complexity of your task and the desired accuracy level. Read more

In the realm of autonomous systems, the use of cutting-edge technologies plays a pivotal role in ensuring efficient and safe operations. This article delves into the integration of YOLO (You Only Look Once) object detection and CSRT (Discriminative Correlation Filter with Channel and Spatial Reliability) tracking to empower an Automated Guided Vehicle (AGV) with advanced capabilities. YOLO for Real-Time Object Detection: In the realm of autonomous systems, the use of cutting-edge technologies plays a pivotal role in ensuring efficient and safe operations. Read more

To run virtualization task on Windows, two of popular hypervisors that come to mind are Windows Hyper-V and Oracle VM VirtualBox. One of the problem is you cannot run both hypervisors software at the same time, and you cannot switch between them without a system reboot. 1 As users of both of these software, we have came out a list of pros and cons for Hyper-V and VirtualBox, so you can decide which hypervisor you would use. Read more

An introduction to ROS and trackless navigation.

Before we first designed our Zalpha AGV, we have delivered quite a number of customized AGV solutions. Learning from our past experience, we decided that we need a software which is flexible to different customizations, yet does not demand our programmers to be on-site to setup the AGVs. The first release of the software (which was later named as NavWiz) was developed within 3 months by our software team, in early 2016. Read more

Welcome to our engineering blog! We hope to share about the amazing stuff we do, we build, and we ❤️ at DF Automation. — Technical Team