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:
I have too many work in the last few months and don't have time to deal with some known bugs of AntOS until now. This v0.2.4-a release focuses on improvement and bugs fix
Applications developed using AntOSDK can be found on this repository: https://github.com/lxsang/antosdk-apps. They can be used as example projects for AntOSDK
WARNING: Due to some recent attacks on my server, the web terminal access is disabled for the user: demo. Someone tried to run a TOR relay on my server using that user, so i decided to disable the terminal access on the demo user. You can still login, but you can't use the shell
This post contains some tips and tricks that helps resolve problems that i've encountered when working with Linux, mostly Ubuntu.
Some of my applications are 32 bits only which sometime depend on several 32 bits libraries. By default, ubuntu installed only the 64 bits version of these libraries. To installed the 32 bit ones, we need enable the i386 architecture using
dpkg, these following commands should be executed as root:
When i developed this blog (using my own client-server platform such as web server, back-end, front-end, etc., built from ash/scratch :) ), i simply designed it as a simple "note book" where i put my ideas or some stuffs that i have done. So, initially, there are no category no advance feature like post suggestion based on current post, etc. It is just a bunch of posts sorting by date. The thing is, i usually work on many different domains (robotic, IoT, backend, frontend platform design, etc.), so my posts are mixed up between different categories. It is fine for me, but is a real inconvenience for readers who want to follow up their interesting category on the blog. Of course, i could redesign the blog and add the missing features by messing around with the relational database design (i'm using SQLite btw), manually classifying the posts in the back-end, etc. But, i'm a kind of lazy people, so i've been thinking of a more automatic solution. How about an automatic document clustering feature based on a data mining approach ? Here we go!
I've had funny time playing around with the Gazebo simulator for autonomous robot exploration. One thing I've encountered is that the odometry data provided by Gazebo is so perfect that, sometime, makes the simulation less realistic. I used a Turtlebot model as robot model in my simulations. Googling around, i didn't find any solution of adding noise to the odometry data of this robot (using the URDF file). I then decided to develop a dedicated ROS node allowing me to add some random noise to the Gazebo's odometry data.
First thing fist, we need to understand the robot motion model. There are many motion models, but in the scope of this article, we focus only on the odometry motion model. Often, odometry is obtained by integrating sensor reading from wheel encoders, it measures the relative motion of the robot between time \(t\) and \(t-1\) or \((t-1,t]\). In 2D environment, a robot pose is represented by a point \((x,y)\) and an orientation (rotation angle) \(\theta\), so the robot pose at the time \(t-1\) and \(t\) are denoted by:
This setup is performed and documented on an Ubuntu system with the following software stack:
sudo apt-get install git)
To follow this post, some basic knowledge on ROS is needed:
A new release of AntOS, it is now in the beta state, but i'll keep the alpha branch on the release for a few further releases.