Cool AI-Empowered Simulation!!!
Physically-based modeling and simulation attempts to map a natural phenomena to a computer simulation program. There are two basic processes in this mapping: mathematical modeling and numerical solution. The goal of this introductory course is to understand both of them. The mathematical modeling concerns the description of natural phenomena by mathematical equations. Differential equations that govern dynamics and geometric representation of objects are typical ingredients of the mathematical model. The numerical solution involves computing an efficient and accurate solution of the mathematical equations. Finite precision of numbers, limited computational power and memory forces us to approximate the mathematical model with simple procedures.
In this course, we will study various techniques to simulate the physical and mechanical behavior of objects in a graphical simulation or a virtual environment. Students will learn about implementation of basic simulation programs that produce interesting results and verify its correctness. The course will cover three basic components in physically-based modeling and simulation:
The goal of this class is to get students an appreciation of computational methods for modeling of motions in the physical and virtual world. We will discuss various considerations and tradeoffs used in designing simulation methodologies (e.g. time, space, robustness, and generality). This will include data structures, algorithms, computational methods and simulation techniques, their complexity and implementation. The lectures will also cover some applications of physically-based modeling and simulation to the following areas:
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LECTURES AND APPROXIMATE SCHEDULE
Here is a list of TENTATIVE lecture topics (subject to changes). Schedule and information on each topic (e.g. readings, web pointers) will be added during the semester before each class.
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COURSE READING MATERIALS
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ASSIGNMENTS AND PROJECTS
The class grade of each student taking 3-credits is determined by
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For more information, contact Ming C. Lin, lin@cs.umd.edu.================================================================================================================================================================================================================================================================================================================
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