CS689 Objectives and Outcomes
Information
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Instructor: Amarda
Shehu amarda\AT\gmu.edu
Class Place and Time: Innovation Hall 136, M 4:30-7:10 pm
Instructor Office Hours: ENGR #4452, M 2:30-4:30 pm
Outcomes
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At the end of this course, students will have been familiarized with methods for a computational treatment of complex physical systems in the presence of geometric and dynamic constraints. Students will be able to implement deterministic and sampling-based approaches for planning motions of robot systems in the presence of obstacles. In particular, students will be able to employ the OOPSMP motion-planning programming platform to implement advanced planning methods that can handle kinodynamic constraints. Selected topics will expand students' understanding of sensor-based motion planning, manipulation planning, assembly planning, planning under uncertainty, and robotics-inspired methods for the modeling and characterization of biological molecules as special articulated chains.
