Introduction and motivation drafts

documentation/tools.tex

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+\chapter{Hardware and Software}
+
+\section{Robot}
+
+The aforementioned \textit{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 makes Nao an attractive development platform, suitable for the task
+of \todo{Robocup}. However, 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 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 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.
+
+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.
+
+\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 NAOqi C++ SDK. Being based on the C++
+language, this SDK can naturally be expected to have better performance and 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 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.
+
+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
+documentation. However, B-Human has been in development over many years and is
+therefore a very complex system. The amount 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.