Course Description
Teaches students to understand the fundamental principles of robotics and expose students to the latest robotics research. The course will cover advanced topics such as differential kinematics, localization, mapping, motion planning, soft robotics, and robotic perception, as well as current research topics in robotics.
Athena Title
Advanced Robotics
Prerequisite
(MATH 2250 or MATH 2250E) and MATH 3000 and permission of department
Semester Course Offered
Offered every year.
Grading System
A - F (Traditional)
Course Objectives
Upon completion of this course, students should be able to: • Explain principles of robotics for manipulators and mobile robots • Apply or design algorithms for robotic perception and scene understanding with 2D and 3D vision, as well as deep learning • Evaluate and compare the current robotics research
Topical Outline
• Forward/inverse/differential kinematics and cartesian control for manipulators and mobile robots • Motion planning: sampling-based and graph-based algorithms • Localization and mapping • Soft robotics • Motion and tracking: optical flow, Kalman filter, Bayes filter, and particle filter • Machine learning and deep learning in scene understanding • Reinforcement learning in robotic control • Literature review of the current robotics research (from top robotics conferences)