This updated edition will help you to work with ROS Hydro and teach you how to create, visualize, and process point cloud information from different sensors. This is a hands-on guide to the fascinating world of robotics which will help you get to grips with controlling and planning the motion of robotic arms with multiple joints using MoveIt.

About the Author:

Enrique Fernandez

Enrique Fernandez has a PhD in computer engineering from the University of Las Palmas de Gran Canaria and is a senior robotics engineer currently working at Clearpath Robotics, Inc. He did his MSc master's thesis in 2009 on SLAM. Enrique addresses the problem of path planning for autonomous underwater gliders (AUGs) in his PhD thesis, which was presented in 2013. During that period, he also worked on Computer Vision, AI, and other robotics topics, such as inertial navigation systems and Visual SLAM at the CIRS/ViCOROB Research Lab of the University of Girona for AUVs. He also participated in the Student Autonomous Underwater Challenge, Europe (SAUC-E) in 2012 and collaborated in the 2013 edition; in the 2012 edition, he was awarded a prize. After his PhD, Enrique joined PAL Robotics in June 2013 as a senior robotics engineer in the Autonomous Navigation department. There, he developed software for REEM, REEM-C, and mobile-based robots and also for corresponding projects, such as Stockbot, using the ROS framework intensively. He worked on motion planning (path planning and control for mobile robots), robot localization, and SLAM. Recently, in 2015, he joined Clearpath Robotics, Inc. to work as a senior autonomy developer on SLAM, within the Autonomy department. From an academic perspective, Enrique has published several conference papers and publications, two of them on the International Conference of Robotics and Automation (ICRA), in 2011. He is also an author of chapters of a few books and a previous book about ROS, Learning ROS for Robotics Programming by Packt Publishing. His MSc master's thesis was about the FastSLAM algorithm for indoor robots using a SICK laser scanner and the wheel odometry of a Pioneer differential platform. His PhD thesis contributed path planning algorithms and tools for AUGs. 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.

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