: cmu-ri-courses-00-01.daml, v 0.1 2001/01/17 21:04:41 terryp Exp $ Instances based on courses offered by the Robotics Institute during the year 2000/2001, defined for HW3. Contact terry@acm.org for details. http://www.cs.cmu.edu/afs/cs/academic/class/15384/web/index.html 15-384 Robotic Manipulation 9 Foundations and principles of robotic manipulation. Topics include computational models of objects and motion, the mechanics of robotic manipulators, the structure of manipulator control systems, planning and programming of robot actions. 15-385 Computer Vision (CS) Tai-Sing Lee 9 Basic concepts in machine vision, including sensing and perception, 2D image analysis, pattern classification, physics-based vision, stereo and motion, and solid model recognition. http://www.cs.cmu.edu/~15781/ 15-781 Machine Learning (CS) 12 Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers the theory and practice of machine learning from a variety of perspectives. We cover topics such as learning decision trees, neural network learning, statistical learning methods, genetic algorithms, Bayesian learning methods, explanation-based learning, and reinforcement learning. The course covers theoretical concepts such as inductive bias, the PAC and Mistake-bound learning frameworks, minimum description length principle, and Occam's Razor. Programming assignments include hands-on experiments with various learning algorithms. Typical assignments include neural network learning for face recognition, and decision tree learning from databases of credit records. http://www.cs.cmu.edu/afs/cs.cmu.edu/academic/class/15882-s00/ 15-882 Introduction to Artificial Neural Networks (CS) 12 A survey of neural net architectures and applications, with an in-depth look at problems in pattern recognition and in knowledge representation. 16-199A Building the Future 4 The goal of this project course is to teach undergraduates (especially freshmen and sophomores) how to build such things as robots and intelligent environments, and how to get involved in research. In the process we will develop our abilities to predict how technology will affect the future. 16-597 Undergraduate Reading and Research Need project supervisor's permission. http://www.cs.cmu.edu/afs/cs/academic/class/16711-s00/web/ 16-711 Kinematics, Dynamic Systems and Control 12 Basic concepts and tools for the analysis, design, and control of robotic mechanisms. Topics covered include foundations of kinematics, kinematics of robotic mechanisms, review of basic systems theory, control of dynamical systems. Advanced topics will vary from year-to-year, including motion planning and collision avoidance, adaptive control, and hybrid control. 16-720 Computer Vision 12 This course deals with the science and engineering of computer vision, that is, the analysis of patterns in visual images of the world with the goal of reconstructing and understanding the objects and processes in the world that are producing them. The emphasis is on physical, mathematical, and information processing aspects of vision. Topics covered include image formation and representation, camera geometry and calibration, multi-scale analysis, segmentation, contour and region analysis, energy-based techniques, reconstruction of based on stereo, shading and motion, 3-D surface representation and projection, and analysis and recognition of objects and scenes using statistical and model-based techniques. The material is based on a recent graduate-level textbook augmented with research papers, as appropriate. The course involves considerable Matlab programming exercises. http://www.cs.cmu.edu/~rcollins/APseminar/APhome.html 16-721 Advanced Perception 12 Advanced issues in robot perception on a rotating basis including sensor design and calibration, model-based and physics-based perception, parallel computing for perception, speech and other non-vision sensors, and perception system design. This class has a major project component in Robotics research labs. http://www.cs.cmu.edu/~sensing-sensors/ 16-722 Sensing and Sensors 12 The principles and practices of quantitative perception (sensing) illustrated by the devices and algorithms (sensors) that implement them. Learn to critically examine the sensing requirements of proposed applications of robotics to real problems, to specify the required sensor characteristics, to analyze whether these specifications can be realized even in principle, to compare what can be realized in principle to what can actually be purchased, to understand the engineering factors that account for the discrepancies, and to design transducing, digitizing, and computing systems that come tolerably close to realizing the actual capabilities of available sensors. To the extent that time and interest permit, in addition to the sensing requirements of robot function (manipulation, mobility) per se, illustrative applications will also be drawn from the domain of observations that robots are employed to make (e.g., noninvasively locating buried objects or skeletal features, or nondestructively characterizing natural or manufactured materials), and the domain of infrastructures that robotic applications depend on (e.g., broadcast communication and navigation signals). http://www.cs.cmu.edu/~awm/731/ 16-731 Fundamentals of AI for Robotics (also CS 15-780) 12 Graduate-level introduction to Artificial Intelligence tailored toward the algorithms and applications of robotics, manufacturing, and engineering disciplines. Strong focus on modern numerical approaches to AI and robotics, including Bayes nets, classical decision-theoretical problems such as scheduling, and optimal and learning control of Markov systems. Motion planning and spatial reasoning, neural nets, qualitative reasoning, and fuzzy logic are covered in detail. 16-732 Computational Statistics of Multidimenstional Scientic Databases 12 The course will provide a unified view of the statistical approaches in a number of different fields like image processing, natural language, information retrieval, code theory, computational biology, diagnosis and decision systems, data mining. It will present what it means to construct and to use a statistical model emphasizing the specific computational problems posed by the multidimensionality of the data and the size of the data sets. The course will include direct investigation in a new area that has grown at the boundary of three different CMU schools (Astrophysics, Statistics and Computer Science) in the past 18 months as a result of the instructors' research collaboration called "Computational AstroStatistics": the development and implementation of new, statistically-robust, and computationally highly efficient tools to support large sky astronomical surveys. http://voronoi.sbp.ri.cmu.edu/~choset//sbp_class98/sbp_class98.html 16-735 Sensor-Based Robotic Motion Planning 9 Sensor based robotic motion planning incorporates sensor information, reflecting the current state of the environment, into a robot's planning process, as opposed to classical motion planning, which assumes the robot has full knowledge of the world prior to the planning event. http://www.cs.cmu.edu/~mason/mech_manip.html 16-741 Mechanics of Manipulation 12 Kinematics, statics, and dynamics of robotic manipulator's interaction with a task, focusing on intelligent use of kinematic constraint, gravity, and frictional forces. Automatic planning based on mechanics. Application examples drawn from manufacturing and other domains. http://www.cs.cmu.edu/~illah/ri761.html 16-761 Introduction to Mobile Robots 12 Components of mobile robots; perception, mechanism, planning, and architecture; detailed case studies of existing systems. 16-762 Field Robotics 12 16-778 Mechatronic Design 12 Mechatronics is the synergistic integration of mechanism, electronics, and computer control to achieve a functional system. Because of the emphasis upon integration, this course will center around laboratory projects in which small teams of students will configure, design, and implement several mechatronic devices or systems. Lectures will complement the laboratory experience with comparative surveys, operational principles, and integrated design issues associated with the spectrum of mechanism, electronics, and control components. http://www.cs.cmu.edu/~me/courses/mathfund.html 16-811 Mathematical Fundamentals for Robotics 12 Fourier transforms, the Nyquist sampling theorem, differential equations, numerical methods, calculus of variations, differential geometry, and related topics. 16-830 Planning, Execution and Learning (also CS 15-887) 12 This course will explore both classical and modern approaches to planning. Issues to be discussed include: how to represent actions and world state, how to search for plans efficiently, how to deal with uncertainty in actions and the world state, how to represent time, and how to dynamically combine planning and execution. Specific planning techniques to be covered include: means-ends analysis, linear and non-linear planning, GraphPlan, SatPlan, hierarchical planning, conditional planning, probabilistic planning using Markov models (MDPs and POMDPs), integration of planning, perception and execution, execution monitoring and replanning, planning and learning, and robot (geometric) planning. There are no explicit prerequisites, but a basic knowledge of AI is assumed. http://www.ece.cmu.edu/~fedder/18-819 16-859 MicroElectroMechanical Systems (MEMS) (also ECE 18-819) 12 The promise of better performance, lower cost, and miniaturization of sensor and actuator systems has motivated growth in the area of MicroElectroMechanical Systems (MEMS): silicon-based integrated microsystems. MEMS technology has broad applications such as inertial navigation, data storage, biochemical analysis, micromanipulation, optical displays, and microfluidic jet systems. This course is an introduction to MEMS, intended for first and second-year graduate students in ECE and Robotics who desire the engineering background necessary for research in MEMS at Carnegie Mellon. 16-861 Mobile Robot Design 18 Mobile Robot Design is a unique course offering in that it allows students to design and build a prototype robot. Prior developments include Skyworker, Dante and lunar rover concepts. The development of a mobile robot requires diverse technical skills and experience. Students will become an integral part of a team of Robotics Institute peers developing a new robot. Through team meetings, guest speakers and system development, students will be exposed to the interrelated effects of electronics, software and mechanisms on the design process. Participants will move a conceptual design from paper to implementation in a fast paced, and multidisciplinary environment. Students will be provided an opportunity to test their ability to apply theoretically sound approaches within the constraints of a real design. Students with interests in artificial intelligence, navigation, path planning, simulation, machine vision, sensor fusion, control, mechanism design and power systems, are encouraged to enroll. Individuals will gain an understanding of the complexities of integrating systems within a robot, and approaches that mitigate the difficulties, in a learn-through-doing environment. Interested students may wish to contact Chris Urmson @ curmson@ri.cmu.edu or x88098. http://www.cs.cmu.edu/~illah/rix62.html 16-862 / 16-362 Introduction to Mobile Robot Programming 12 This course is a complete, hands-on introduction to Mobile Robot Programming. Using six Nomad Scout robots and portable computers, we will survey topics ranging from low-level control and obstacle avoidance, including PID control, to high-level navigation, planning, robot-robot communication and cooperation. 16-863 / 16-363 Advanced Mobile Robot Programming 12 Advanced Mobile Robot Programming is an advanced research and development course for graduates of 16362 and 16862. In this class, teams of students conduct research and prototype working robot architectures that are research-quality. The best robot systems are generally demonstrated at the National Conference on Artificial Intelligence. 16-864 Humanoids 12 This seminar will discuss both virtual and robotic humanoids. We will try to identify what we know about humans that can help us program humanoids, and what we know about humanoids that will help us understand ourselves. Readings will be drawn from a wide range of fields. http://www.coral.cs.cmu.edu/amrs/ 16-869 Autonomous Multirobot Systems (also CS 15-889) 12 Multiple redundant robots provide more reliable solutions to real-world tasks than a single agent because the overall system is less sensitive to failure. Reliability is not the only benefit multirobot systems offer; multirobot teams can provide significant performance advantages as well. In order to realize increased performance however, the system designer must address a number of new challenges presented by the multirobot domain. 16-899A Agents, Embodiment and Interaction 12 This course will deal with these and associated issues through readings drawn from Cognitive Science, Computer Science, Artificial Intelligence, Artificial Life, HCI, Science Studies, Cultural Studies, Electronic Media Theory and Art Theory, by such authors as Philip Agre, Francisco Varela, Rodney Brooks, Katherine Hayles, Brian Winston, Kerstin Dautenhahn and others. 16-899B Telepresence Art and Applications 10 Multidisciplinary class that explores the use and creation of perception and control devices (telerobots) to filter a user's relationship to an experience, whether in close or remote locations. Such a process alters the relationship between viewer and viewed object / event. Includes the design and construction of tele-robotic / -presence systems and the development of mechanical, electronic, programming, theoretical, and aesthetic skills. Experience with electronics and / or mechanics is desirable but not a pre-requisite, as is familiarity with contemporary art. Class will produce art projects as well as concepts for applied (consumer) purposes. 16-899C Robotic Art Studio 12 Robotic Art Studio is an interdisciplinary course offered with both Computer Science and Art numbers. It explores the use of embedded microcontrollers and robotic technologies in programmed behaving artworks. The class takes robotic technol ogies as its content, but its form is based on the traditional art studio where imagination, self discipline and self directed research are crucial skills. 16-995 Independent Study For Robotics graduate students only. 16-997 Reading and Research For Robotics graduate students only.