Skip to main content

Research

Controls

We lead controls research, the design of algorithms and techniques to enable systems to independently perceive, reason, and act within their environment.

We offer courses in the guidance, navigation, and control of unmanned aerial systems as well as the optimization and control of networked systems. We are leaders in research in control of autonomous systems, bio-inspired engineering, model predictive control, dynamical modeling, and estimation for single and distributed systems. We develop tools that address the temporal, spatial and nonlinear challenges posed by autonomy.

A&A undergrad and graduate students have the opportunity to explore practical applications for autonomy by gaining hands-on flight-testing and field operations experience with interdisciplinary collaborators and partners.

Behçet Açikmeşe

Key research areas

  • Automatic control
  • Autonomous vehicle control
  • Control theory
  • Dynamics and optimization
  • Flight operations
  • Underwater vehicle design
  • Unmanned aerial systems

Associated faculty

Research highlights

A successful Mars rover landing ends with a crash

A&A’s Behcet Açıkmeşe helped develop hurling algorithms to land NASA's rovers Curiosity and Perseverance. 

A&A's Research Takes Flight

A&A research will get the rare opportunity to fly in real flight conditions on the 2021 Boeing ecoDemonstrator.

Hide and Seek

The Autonomous Flight Systems Lab builds a drone-based machine learning dataset to find those lost in the wilderness.

Award-winning student team

A&A’s Charlie Kelly and Taylor Reynolds launched the A&A CubeSat Club, with support from Aeroject Rocketdyne. The club is developing its first satellite, SOC-i, that will reconcile constraints in its orientation and imaging systems. With these capabilities, SOC-i will be a step toward comprehensive environmental monitoring.

Related News

Mon, 04/22/2019 | Department of Aeronautics & Astronautics

RAIN Lab's research on the science of sync published in Science

Research on sync and the structure of networks by the RAIN Lab, led by Mehran Mesbahi, was published in Science.

 

Wed, 10/10/2018 | Department of Aeronautics & Astronautics

A&A drone mapping project advances wildfire modeling

A&A’s Autonomous Flight Systems Lab is partnering with the US Forest Service to improve the efficiency of data collection for wildfire modeling.