assigned the portions
This commit is contained in:
84
documentation/Yuankai/tools.tex
Normal file
84
documentation/Yuankai/tools.tex
Normal file
@@ -0,0 +1,84 @@
|
||||
\chapter{Hardware and Software}
|
||||
|
||||
\section{Robot}
|
||||
|
||||
The aforementioned Nao \cite{nao} is a small humanoid robot, around 60
|
||||
cm tall. Some of its characteristics are:
|
||||
|
||||
\begin{itemize}
|
||||
|
||||
\item Two HD-cameras on the head
|
||||
|
||||
\item An ultrasonic rangefinder on the body
|
||||
|
||||
\item An inertial navigation unit (accelerometer and gyroscope)
|
||||
|
||||
\item Internet connectivity over Ethernet cable or 802.11g WLAN
|
||||
|
||||
\item Single-core Intel Atom CPU and 1 GB of RAM
|
||||
|
||||
\item Programmable joints with overall 25 degrees of freedom
|
||||
|
||||
\item Speakers
|
||||
|
||||
\item 60 to 90 minutes battery life.
|
||||
|
||||
\end{itemize}
|
||||
|
||||
It can be seen from the specifications list, that the multitude of sensors and
|
||||
interfaces make the Nao an attractive development platform, suitable for the task
|
||||
of playing soccer. However, a relatively weak CPU and a low amount of RAM require
|
||||
the programs running on the robot to be resource-efficient, which had to be
|
||||
taken into account during our work on the project.
|
||||
|
||||
\section{Software}
|
||||
|
||||
In our project we used \textit{NAOqi OS} as an operating system for the robot.
|
||||
This is a standard operating system for Nao robots based on Gentoo Linux, and
|
||||
it can handle all aspects of robot control, such as reading the sensors, moving
|
||||
the robot and establishing the network connection.
|
||||
|
||||
As a framework for the implementation of the desired behavior we chose the
|
||||
official \textit{NAOqi Python SDK} \cite{naoqi-sdk}. We found this framework
|
||||
easy to use, well documented and also covering most basic functionality that
|
||||
was necessary for us to start working on the project. A further advantage of
|
||||
this SDK is that it uses Python as the programming language, which allows for
|
||||
quick prototyping, but also makes maintaining a large codebase fairly easy.
|
||||
|
||||
Finally, the third-party libraries that were used in the project are
|
||||
\textit{OpenCV} and \textit{NumPy} \cite{opencv, numpy}. OpenCV is a powerful
|
||||
and one of the most widely used open-source libraries for computer vision
|
||||
tasks, and NumPy is a popular Python library for fast numerical computations.
|
||||
Both of these libraries, as well as the NAOqi Python SDK are included in the
|
||||
NAOqi OS distribution by default, which means that no extra work was necessary
|
||||
to ensure their proper functioning on the robot.
|
||||
|
||||
\section{Rejected Software Alternatives}
|
||||
|
||||
Here we will briefly discuss what alternative options were available for the
|
||||
choice of the base framework, and why we decided not to use those. One
|
||||
available option was the official \textit{NAOqi C++ SDK}. Being based on the
|
||||
C++ language, this SDK can naturally be expected to have better performance and to be more resource-efficient, than the Python-based version. We still chose the
|
||||
Python SDK, because C++ is not particularly suitable for fast prototyping,
|
||||
because of the complexity of the language. It is also worth noting, that we
|
||||
never really hit the performance constraints, that couldn't have been overcome
|
||||
by refactoring our code, but in the future it might be reasonable to migrate
|
||||
some portions of it to C++.
|
||||
|
||||
Another big alternative is \textit{ROS} \cite{ros} (Robotic Operating System).
|
||||
ROS is a collection of software targeted at robot development, and there exists
|
||||
a large ecosystem of third-party extensions for ROS, which could assist in
|
||||
performing common tasks such as camera and joint calibration, as well as in
|
||||
more complex tasks such as object detection. ROS was an attractive option, but
|
||||
there was a major downside, that there was no straightforward way to run ROS
|
||||
locally on the robot, so the decision was made not to spend time trying to
|
||||
figure out how to do that. However, since Python is one of the main languages
|
||||
in ROS, it should be possible in the future to incorporate our work into ROS.
|
||||
|
||||
Finally, as was already mentioned in the introduction, \textit{B-Human
|
||||
Framework} is a popular choice for beginners, thanks to the quality of the
|
||||
algorithms and good documentation. However, B-Human has been in development
|
||||
over many years and is therefore a very complex system. The amount of time needed
|
||||
to get familiar with the code, and then to incorporate our changes would have
|
||||
been too big. For this reason we decided to use the simpler option as a
|
||||
starting point.
|
||||
Reference in New Issue
Block a user