Robotics in the Classroom - NASA.
In this lecture I will describe the mathematics of machine learning and explain its applications to robotics. In particular I will show how the modern ideas of deep learning allow a robot to make sense of the world it exists in, including the ideas behind speech and face recognition.
Prompt: Interest in math, science, or engineering manifests itself in many forms. Caltech professor and Nobel Laureate Richard Feynman (1918-1988) explained, 'I'd make a motor, I'd make a gadget that would go off when something passed a photocell, I'd play around with selenium'; he was exploring his interest in science, as he put it, by 'piddling around all the time.'.
Every day after school, our robotics workstation (a messy garage) became our haven as we labored to find the best design for our robot. Scattered across the floor were sheets of engineering design, details of mathematical formulas, and heaps of extra pieces as we tried to determine the best heuristic algorithm and design for our robot.
A2A. The essential prerequisites are: - calculus - ordinary differential equations - linear algebra (you need a very strong background in linear algebra) - numerical methods (not numerical analysis) You can then branch out. Typically, a robotic.
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Mathematics and Robotics Image of Honda's humanoid robot, ASIMO via Wikipedia. Aside from their popularity in science fiction and dystopian literature, robots play many important roles in society today, from handling hazardous materials to welding components, performing surgery, or vacuuming carpets.