Johns Hopkins University 3 credits Computer Science
This course explores advanced topics in navigation, perception, mapping, and control for mobile robots. Mathematical models of commonly used sensors such as wheel tachometers, accelerometers, gyroscopes, radio frequency transceivers, monocular visual cameras, laser scanners, and LiDAR imagers will be developed. Planar and 3D vehicle motion models will be derived in both deterministic and stochastic settings. Navigation algorithms covered in the course include dead reckoning, beacon localization, beacon simultaneous localization and mapping (SLAM), monocular visual camera based SLAM, and monocular visual camera + inertial sensor based SLAM. A survey of relevant stability/control theory, estimation theory, projective geometry, and image processing algorithms will be provided. Students will be exposed to these topics through course lectures, weekly homework assignments, and a term-long robotics hardware project. Prerequisite(s): EN.605.613 β Introduction to Robotics or equivalent introductory robotics course.
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