DescriptionIntroduction: The field of mobile robotics has grown tremendously in the last decade. Examples of the major achievements include the vehicles competing in the Darpa Grand Challenge or the Google cars that are deployed in the United States and are used to map many cities in the US. Inline with this growing interest in autonomous navigation, this workshop is intended to give its participants a hands-on experience in building and programming robots for navigation. PROGRAM The intent of this 5-day workshop is to introduce students to the world of autonomous mobile robotics. The format of the workshop consists of lecturing in the mornings and hands-on activities in the afternoons. The programming and interface for the course will be that of an embedded system such as an Arduino or Waspmote microcontrollers. Day 1 AM (lectures): introduction to mobile robotics (general overview) Day 1 PM (applied): introduction to programming on embedded systems (e.g., Arduino or Waspmote etc.) Day 2 AM (lectures): modeling of robots & sensor theory Day 2 PM (applied): modeling & Sensor integration on an embedded system (sonars, touch sensors, IR sensors, cameras) Day 3 AM: (lectures): motion modeling and localization DAY 3 PM (applied): motion modeling on an embedded system (platforms such as Tetrix/Pitsco hardware kits) DAY 4 AM (lectures): Simultaneous Localization and Mapping (SLAM) DAY 4 PM (applied): SLAM on an embedded system DAY 5 AM (lectures): path planning using Anytime Dynamic (AD) DAY 5 PM (applied): AD on an embedded system HARDWARE & SOFTWARE Hands-on activities will be implemented on an Arduino prototype platform (to be decided after consulting with KAUST) More specifically the hardware and software consists of the following: Hardware: • Arduino or Waspmote platforms • Hardware to build robots such as Tetrix/ Pitsco kits, or Vex Robotics. Software: • After deciding on the exact hardware that will be used for the training, corresponding software will be selected. Accordingly we will be using either the Arduino programming language, Matlab, or C for Vex. PREREQUISITE Although the course covers most concepts from first principles, it is aimed at graduate students who possess some basic knowledge of probability theory and programming skills. More specifically people with the following knowledge will feel more comfortable in this course • Basic knowledge in probability theory • Basic programming skills (C, C++, Matlab) • Basic knowledge of electronics • Basic knowledge of microcontrollers
Daniel Asmar is an Assistant Professor in Mechanical Engineering at the American University of Beirut. Daniel received his Bachelors degree in Mechanical Engineering from the University of Waterloo in 1993. He later earned his Master’s degree in Mechanical Engineering from the American University of Beirut in 2002, and his Ph.D. in Systems Design Engineering from the University of Waterloo in 2006. Daniel’s research interests are in Robotics and Computer Vision. Specifically, he has interests in visual perception, autonomous robot navigation and mapping, environment representation and recognition, and segmentation methods in Computer Vision. He has several publications in these areas in refereed journals and conference proceedings. Daniel also has working experience in industry in mechanical and industrial design.
Sevag Babikian is an instructor at the mechanical engineering department in the Faculty of Engineering and Architecture at the American University of Beirut (AUB). He graduated with a Bachelor of engineering in mechanical engineering from AUB, pursued a master’s degree in mechatronics and robotics, with research involved in the gait generation of under-actuated robotic systems. Sevag’s personal projects and work experience cover interactive mechatronic and industrial robotic systems. His interests lie in development of automated systems and heis currently working on the design of robotic systems for the Lebanese and regional industrial sectors.
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