The book will take an easy-to-follow and engaging tutorial approach, providing a practical and comprehensive way to learn ROS. If you are a robotic enthusiast who wants to learn how to build and program your own robots in an easy-to-develop, maintainable and shareable way, "Learning ROS for Robotics Programming" is for you. In order to make the most of the book, you should have some C++ programming background, knowledge of GNU/Linux systems, and computer science in general. No previous background on ROS is required, since this book provides all the skills required. It is also advisable to have some background on version control systems, like svn or git, which are often used to share the code by the community.
Aaron Martinez
Aaron Martinez is a computer engineer, entrepreneur, and expert in digital fabrication. He did his Master's thesis in 2010 at the IUCTC (Instituto Universitario de Ciencias y Tecnologias Ciberneticas) in the University of Las Palmas de Gran Canaria. He prepared his Master's thesis in the field of telepresence using immersive devices and robotic platforms. After completing his academic career, he attended an internship program at The Institute for Robotics in the Johannes Kepler University in Linz, Austria. During his internship program, he worked as part of a development team of a mobile platform using ROS and the navigation stack. After that, he was involved in some projects related to robotics, one of them is the AVORA project in the University of Las Palmas de Gran Canaria. In this project, he worked on the creation of an AUV (Autonomous Underwater Vehicle) to participate in the Student Autonomous Underwater Challenge-Europe (SAUC-E) in Italy. In 2012, he was responsible for manufacturing this project; in 2013, he helped to adapt the navigation stack and other algorithms from ROS to the robotic platform.
Recently, Aaron created his own company called Biomecan. This company works with projects related to robotics, manufacturing of prototypes, and engineering tissue. The company manufactures devices for other companies and research and development institutes. For the past two years, he has been working on engineering tissue projects, creating a new device to help researchers of cell culture.
Aaron has experience in many fields such as programming, robotics, mechatronics, and digital fabrication, many devices such as Arduino, BeagleBone, Servers, and LIDAR, servomotors, and robotic platforms such as Wifibot, Nao Aldebaran, and Pioneer P3AT.
Enrique Fernández
Enrique Fernández is a computer engineer and roboticist. He did his Master's Thesis in 2009 at the University Institute of Intelligent Systems and Computational Engineering in the University of Las Palmas de Gran Canaria. There he has been working on his Ph.D for the last four years; he is expected to become a Doctor in Computer Science by September 2013. His Ph.D addresses the problem of Path Planning for Autonomous Underwater Gliders, but he has also worked on other robotic projects. He participated in the Student Autonomous Underwater Challenge-Europe (SAUC-E) in 2012, and collaborated for the 2013 edition. In 2012, he was awarded a prize for the development of an underwater pan-tilt vision system.
Now, Enrique is working for Pal-Robotics as a SLAM engineer. He completed his internship in 2012 at the Center of Underwater Robotics Research in the University of Girona, where he developed SLAM and INS modules for the Autonomous Underwater Vehicles of the research group using ROS. He joined Pal-Robotics in June 2013, where he is working with REEM robots using the ROS software intensively and developing new navigation algorithms for wheeled and biped humanoid robots, such as the REEM-H3 and REEM-C.
During his Ph.D, Enrique has published several conference papers and publications. Two of these were sent to the International Conference of Robotics and Automation (ICRA) in 2011. He is the co-author of some chapters of this book, and his Master's Thesis was about the FastSLAM algorithm for indoor robots using a SICK laser scanner and the odometry of a Pioneer differential platform. He also has experience with electronics and embedded systems, such as PC104 and Arduino. His background covers SLAM, Computer Vision, Path Planning, Optimization, and Robotics and Artificial Intelligence in general.
