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Pavel Lutskov
2018-08-08 10:34:15 +02:00
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documentation/tools.tex
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@@ -2,8 +2,8 @@
\section{Robot}
The aforementioned \textit{Nao} is a small humanoid robot, around 60 cm tall.
Some of its characteristics are:
The aforementioned \textit{Nao} \cite{nao} is a small humanoid robot, around 60
cm tall. Some of its characteristics are:
\begin{itemize}
@@ -39,19 +39,20 @@ 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 NAOqi Python SDK. Our experience with this framework is that it is
easy to use, well documented and also covers 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.
official NAOqi Python SDK \cite{naoqi-sdk}. Our experience with this framework
is that it is easy to use, well documented and also covers 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 OpenCV and
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.
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}
@@ -66,14 +67,14 @@ 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 of the portions of it to C++.
Another big alternative is 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. 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 to incorporate our work into ROS.
Another big alternative is 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. 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 to incorporate our work into ROS.
Finally, as was already mentioned in the introduction, B-Human Framework is a
popular choice for beginners, thanks to the quality of the algorithms and good