CSE483: Mobile Robotics | Monsoon 2020
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Mobile Robotics: Navigating from Theory to Application
The course introduces the student to fair detail on the basic modules for antomating a mobile robot such as state estimation, visual odometry and mapping, graph based optimization. The course draws upon state of the art practices in probability and statistical methods, optimization techniques and shows how they are dovetailed to a robotics setting. The course has a strong coding component accompanied with conceptual questions in the form of assignments and projects wherein the student is expected to understand, simulate and implement the algorithms taught in class.
At the end of the course, the student is expected to be aware of basic mobile robotic algorithms and should feel comfortable reading and assimilating state of the art research papers in areas covered in the course/class.
Necessary:
It's not mandatory but it helps to have basic knowledge of theory behind optimization methods such as Gradient descent, Newton's method etc.
Transformations: Coordinate Frames, Descriptions, Rotation Matrix, Euler Angles, Axis Angles, Quaternions.
Map representations: Point clouds (Planar and 3D), point clouds in global frame, Occupancy Maps, Octomaps, Signed Distance Fields (SDFs). Point Cloud Registration.
Least Squares and Non Linear Least Squares, Linearization, Jacobian.