Control theory for safe, reliable, and performant autonomous systems.

The Autonomy, Controls, and Robotics Engineering (ACRE) Lab at NC State University.

What we do

The Autonomy, Controls, and Robotics Engineering (ACRE) Lab is a research lab in the Department of Electrical and Computer Engineering at NC State University. We use tools from control theory to build trustworthy autonomous systems. Our vision is to design algorithms for autonomous systems with goal of ensuring that such systems are:

Safe. Formally ensure that autonomous systems operate within strict user-defined limits, backed by rigorous mathematical guarantees.

Reliable. Behave as expected even in the presence of disturbances, model errors, and other sources of uncertainty.

Performant. Autonomous systems that are not just safe but that are also highly dynamic and efficient, capable of completing complex tasks.

News

Date	Title
Oct 22, 2026	CDC Workshop on Safety Analysis for Autonomous Systems
Oct 12, 2026	Max gives a talk at the Technical University of Munich
Oct 8, 2026	Welcome to the new ACRE Lab website
Aug 25, 2026	Max gives a talk at UNC, Chapel Hill
Aug 15, 2026	Yichun joins the ACRE Lab as a PhD student

Recent publications

[1]

M. Mirtaba and M. H. Cohen, “High Order Tuners for Adaptive Safety of Robotic Systems,” in Proceedings of the IEEE Conference on Decision and Control, 2026.

[2]

M. H. Cohen, P. Ong, P. Mestres, and A. D. Ames, “Safety Filtering with an Infinite Number of Constraints,” in Proceedings of the IEEE Conference on Decision and Control, 2026.

[3]

H. Wang et al., “Unified Overview of Safety Certificate Functions: Techniques from Hamilton–Jacobi Reachability and Control Barrier Functions,” in Proceedings of the IEEE Conference on Decision and Control, 2026.

[4]

S. S. Mousavi, M. H. Cohen, P. Mestres, and A. D. Ames, “Structure, Feasibility, and Explicit Safety Filters for Linear Systems,” arXiv Preprint arXiv:2604.04235, 2026.

[5]

M. Mirtaba and M. H. Cohen, “Vector Field Following for Quadrotors via Reduced Attitude Representations with Applications to Safety-Critical Control,” arXiv Preprint arXiv:2610.06629, 2026.

All publications

Research highlights

Safe Vector Field Following on Quadrotors

Embedding safe low-dimensional vector fields into complex dynamics using geometric control methods. Read the paper.

Learning for Layered Safety-Critical Control

Learning to safely control a 3D hopping robot using predictive forward simulation and control barrier functions. Read the paper