Autonomous Systems

Duke MEMS researchers are at work on new control, optimization, learning, and artificial intelligence (AI) methods for autonomous dynamical systems that can make independent intelligent decisions and learn in uncertain, unstructured, and unpredictable environments. We design autonomous systems that span robotics, cyber-physical systems, internet of things, and medicine.

Research Areas

Autonomous medical devices and systems
Control theory and optimization
Cyber-physical systems
Human-autonomy systems
Machine learning (ML) and artificial intelligence (AI)
Networked and distributed systems
Robotics, autonomous systems, surgical robotics
Nonlinear dynamics and systems

Major Centers & Initiatives

Externally funded efforts in autonomy which Duke leads, or is a partner, include:

Related Study Opportunities

PhD

Specializations include:

Master of Science (MS) or Master of Engineering (MEng)

Concentrations include:

Highlights

More MEMS research news

Three surgeons stand around a bed with a mannequin surrounded by machinery

Cross-Training Graduate Students to Develop Smart Robotic Surgical Instruments

Duke’s new NSF Research Traineeship Program brings engineers and computer scientists into the operating room to solve unmet surgical challenges

A tangled mess of blue lines criss-crossing a 3D graphical space with one red line zig-zagging through it

Coordinating Complex Behaviors Between Hundreds of Robots

A new approach to designing motion plans for multiple robots grows “trees” in the search space to solve complex problems in a fraction of the time

astronaut after having blood drawn from arm

NASA Climbs Aboard with Support for Robot Project

The robot can autonomously place an IV in an astronaut’s arm for crewed space missions and to improve access to healthcare on Earth.

Associated Faculty

Leila Bridgeman

Assistant Professor of Mechanical Engineering and Materials Science

Research Interests: Robust and optimal control, linear matrix inequalities (LMIs), model predictive control (MPC), delayed systems, input-output stability, passivity.

Boyuan Chen

Assistant Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science

Research Interests: Robotics, computer vision, machine learning, AI for science

Brian Mann

Professor in the Department of Mechanical Engineering and Materials Science

Research Interests: Nonlinear dynamics and vibration utilizing analytical, numerical, and experimental techniques. Fundamental investigations of phenomenon and application areas where dynamical systems theory plays an important role.

Xiaoyue Ni

Assistant Professor of Mechanical Engineering and Materials Science

Research Interests: Flexible electronics, precision measurement, non-destructive testing, deformation physics of random media, mechanical metamaterials, robotic materials and smart structures, machine learning

Rebecca Simmons

Associate Professor of the Practice in the Department of Mechanical Engineering and Materials Science

Lawrence N. Virgin

Professor of Mechanical Engineering and Materials Science

Research Interests: Study of the behavior of nonlinear dynamical systems, including the investigation of the fundamental nature of nonlinear systems based on a mathematical description of their underlying equations of motion and the application of recent results from nonlinear dynamical systems...