Robotics Engineering Courses

In RBE 595 - Advanced Surgical Robotics, you will learn about the most recent advances in surgical robot technology, and how these advances enable new treatment options for medical conditions that are currently considered inoperable. Topics covered in the course will include: design and control of surgical robotic instruments (with special emphasis on continuum designs), surgeon-robot interaction, supervised surgical robot autonomy, image-guided navigation. In addition to technical lectures, the course involves monthly invited seminars from physicians who provide an overview of select clinical procedures and share their perspective on how robotics can help enhance interventional processes for the benefit of patients.The course culminates in a final team project aimed to develop a grant proposal for a new medical robot. The project typically involves collecting preliminary data and/or working on new designs/simulations to support the scientific rationale of the proposal. The proposal is in the National Institutes of Health (NIH) R21 format.

Mathematical models and the tools of high-level logic (first and second order) have been used to guide specification, development, and verification of software and hardware systems in robot systems and other cyber-physical systems. Because of the high cost of application and complex task specifications, formal methods are introduced for verifying and synthesizing provably correct controllers in robotics. This course provides an exposition to formal methods and their connections with control, optimization, machine learning, and game theory. Topics may include automata theory, temporal logic, abstraction-based control, hybrid systems, probabilistic model checking, deductive verification, game theory and reactive synthesis. Students are expected to propose and complete course projects demonstrating their understanding of the topics.

Prerequisite: Foundations of probability and random variables; Linear algebra; Differential equations; control theory as in ECE 504 or RBE 502; Foundation of computer science (computational models, formal languages, complexity theory) or consent of the instructor.

This hands on course covers smart materials and actuation, with an emphasis on electroactive polymer (EAP) based materials and actuators, such as contractile EAPs, dielectric elastomers (DEAs), and ion-polymer metal composites (IPMCs). Piezoelectric materials and shape memory alloys (SMAs) are included in the course, as well as pneumatic actuation. Because smart materials and electroactivity are relatively new fields, the course involves literature reviews. Each team project will involve two different types of smart materials, where at least one smart material is electroactive. For the team projects, the class will be organized into groups, ensuring that each group had a mixture of different discipline.