Github: https://github.com/lxsang/antos branch antos-1.0.0a
Demo: https://app.iohub.dev/antos/ using user name and password: demo/demo
If one wants to run AntOS VDE locally in their system, a docker image is available at:
API Documentation: https://doc.iohub.dev/antos
It has been a long time since version 0.x.x and now AntOS hits a major changes in its API. From version 1.0.0, AntOS no longer depends on Riot.js in its core UI API. This version introduces a brand new AntOS UI API called AFX API which is rewritten from bottom up. The entire AntOS core API is rewritten in Typescript (from Coffeescript) for better debugging, code maintenance and documenting.
Browser support: tested on Chrome, Firefox and partly Safari. Any browser that supports custom elements API should work. May have problem with Microsoft Edge.
Rust is a modern programing language which is claimed to be blazingly fast and memory-efficient. It syntactically similar to C++, but is designed to provide better memory safety while maintaining high performance and productivity:
Ladies and gentlemen, please meet "Dolly the robot", the first version of my DIY mobile robot. My goal in this DIY project is to make a low-cost yet feature-rich ROS (Robot Operating System) based mobile robot that allow me to experiment my work on autonomous robot at home. To that end, Dolly is designed with all the basic features needed. To keep the bill of material as low as possible, i tried to recycle all of my spare hardware parts.
PhaROS is a collection of Pharo libraries that implements the ROS (Robot Operating System ) based client protocol. It allows developing robotic applications right in the Pharo environment by providing an abstract software layer between Pharo and ROS. This guide makes an assumption that readers already have some basic knowledge about ROS, if this is not the case, please check the following links before going any further on this page:
Doing a research work in robotic domain using Pharo as a prototype and implementation tool (via phaROS) is a whole new experience. It is quite impressive to see how quick an implementation idea becomes a working prototype/solution in Pharo thanks to its productive development environment. Most of my robotic applications are critical tasks which require real-time performance, some of them are heavily resource-demanding (CPU). Due to the single process nature of Pharo, running these tasks on the same VM results in a performance bottleneck, thus sometime, violate the real-time requirement of the application. Common solution to this problem is to dispatch these tasks to several native system processes to boost the performance. Unfortunately, this feature is not supported in current Pharo. My goal in this case is to have something that allow to:
And that is when SystemProcess plays its role.
I use Unix terminal a lot in work, when i work with Pharo and ROS (PhaROS), switching regularly between Pharo and native terminal application (for ROS command line) is kind of inconvenient. I've been thinking of using a terminal emulator application for Pharo. Googling around, i found out that there is no such thing that is ready for production work on modern Pharo, except a prototype work of Pavel Krivanek available at: https://github.com/pavel-krivanek/terminal. However, that code is messy, buggy, and not ready for production work . So i decided to take my time to work on it.
As with AntOS and its applications, one can remotely access and edit server resources from browser in a desktop-like manner. However, sometime these web based applications are not enough for some specific tasks. For a long time, I've thinking of a web based API for controlling remote desktop right from the browser ( or AntOS application). The VNC protocol is a good starting point. After playing around with libvncserver/libvncclient, i came up with wvnc a web based protocol and API for accessing VNC servers using websocket.
This is a demonstration of my current work on controlling robot using ROS and PhaROS. For that task, I've developed a dedicated PhaROS package that defines:
When evaluating the performance of a SLAM algorithm, quantifying the produced map quality is one of the most important criteria. Often, the produced map is compared with (1) a ground-truth map (which can be easily obtained in simulation) or (2) with another existing map that is considered accurate (in case of real world experiment where the ground-truth is not always available ).
Basically, grid maps are images, so image similarity measurement metrics can be used in this case. In this post, we consider three different metrics: Mean Square Error (MSE), K-nearest based normalized error (NE) and Structure Similarity Index (SSIM)
AntOS provides an abstract API for application development. The core API contains three main elements: the UI API, the VFS API and the VDB API, as shown in the following graph: