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Kryodus

Advanced mechanics (lagrange + hamilton) vs Vector based mehanics

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Im an undergraduate student majoring in computing and minoring in physics and I was wondering if I should bother taking third year advanced mechanics course. Im planning to be a video game developer and havent decided whether I want to focus on AI or developing physics engines. Apparently the third year course uses lagrangian techniques to solve problems rather than heavily relying on vectors. Ive done a first and second year mechanics course, and this is the third and final year (for mechanics that is) course. Im not entirely sure what they are, but I was wondering if they are commonly used when developing physics engines, or are merely used to solve problems. Should I bother taking this course say instead of a wave mechanics or semi conductor course? *i dont have much room left for physics courses so I cant take them all :)*

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Lagrange-Hamilton is quite useful for doing mechanics in the presence of constraints - say, human joints. However, I'm not convinced you can make an engine general enough to be useful for games, because you have to translate between the generalised variables used in the Lagrangian, and the actual position variables you want, and this needs to be done pretty much on a case-by-case basis. You could easily program any given joint, but you would end up with a bunch of special cases instead of being able to say "Part A and Part B are joined at point X".

However, this is my instant take on it after two minutes of reflection. If you are more skilled than me, you might be able to use lagrangian mechanics generally. Or even if you aren't; two minutes isn't very much thought, after all.

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I definitely recommend this course if you want to work on physics engines. You should learn about constraints and constraint forces. Understanding generalized coordinates will give you a deeper understanding of the many possible formulations available for modeling a dynamics problem.

If you want to earn brownie points, ask the lecturer about symplectic integration.

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