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Robotics: Home CS521: Robotics Room 8-345 T/Th, 3:00pm - 4:50pm Winter 2017 CS521 home page Instructor: • Office: 8-11 • Email: ftang AT cpp.edu • Phone: (909) 869-2157 • Office Hours: W: 2pm - 4pm, Th: 1pm - 3pm (8-11). Class Email List: Course Description: Software for intelligence robotics. Robot control paradigms. Robotic behaviors. Navigation, planning, localization, and mapping. Prerequisites: CS 241 (or equivalent) and CS 256 (or equivalent) with grades C or better and ability to program in a Linux environment.
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Laboratory for Computational Sensing and Robotics The Laboratory for Computational Sensing and Robotics (LCSR) is one of the most technologically advanced robotics research centers worldwide, and is an international leader in the areas of medical robotics, autonomous systems, and bio-inspiration. Within Johns Hopkins, a premiere research university, the LCSR is a hub for innovative and interdisciplinary robotics engineering, research, and development. The LCSR brings a core group of scholars and students from the Whiting School of Engineering together with researchers from the Johns Hopkins School of Medicine, the Bloomberg School of Public Health, the Krieger School of Arts and Sciences, the Johns Hopkins University Applied Physics Laboratory and the Kennedy Krieger Institute to focus on the common purpose of creating knowledge and fostering innovation. The field of robotics integrates sensing, information processing, and movement to accomplish specific tasks in the physical world. As such, it encompasses several topics, including mechanics and dynamics, kinematics, sensing, signal processing, control systems, planning, and artificial intelligence. Applications of these concepts appear in many areas including medicine, manufacturing, space exploration, disaster recovery, ordinance disposal, deep-sea navigation, home care, and home automation. The faculty of the Laboratory for Computational Sensing and Robotics (LCSR), in collaboration with the academic departments and centers of the Whiting School of Engineering, offers a robotics minor in order to provide a structure in which undergraduate students at Johns Hopkins University can advance their knowledge in robotics while receiving recognition on their transcript for this pursuit.
The minor is not “owned” by any one department, but rather it is managed by the LCSR itself. Hp P2015d Driver Windows 10 there. Any student from any department within the university can work toward the minor.
Robotics is fundamentally integrative and multidisciplinary. Therefore, any candidate for the robotics minor must develop a set of core skills that cut across these disciplines, as well as obtain advanced supplementary skills.
Core Skills Include the Following • Robot kinematics and dynamics (R) • Systems theory, signal processing and control (S) • Computation and sensing (C) Supplementary advanced skills may be obtained in specialized applications, such as space, medicine, or marine systems; or in one of the three core areas listed above. The full minor course listing, provided below and available at, specifies which courses fulfill these requirements. Note that ALL core areas must be covered, but that ANY advanced/supplementary courses can be chosen from the list. This allows students to strike a balance between breadth and depth.
Requirements An undergraduate qualifies for the minor provided he or she has taken at least 18 credits (at the 300-level or above, with a C- or above) from an approved list of courses available below and at with the following requirements and restrictions: • Between 6 and 12 credits chosen to cover the three core skills (R, S, C). • At least 6 credits chosen from advanced supplementary skills (Sup). • At least 3 credits of the 18 must be a laboratory course (Lab) (at least 15 hours of laboratory time that includes working with physical hardware and/or real data). At most 3 credits of the 18 can be an independent research or individual study with a faculty member on the list of approved faculty advisers. • At least 6 credits must be primarily listed in a department other than the student’s home department (it is acceptable if such a course is cross-listed in the student’s home department).