Trajectory Optimization
Onboard trajectory generation in real time for landing, rendezvous, and proximity operations under hard state and control constraints.
Optimization-based autonomy for aerospace systems
We develop convex-optimization methods for trajectory planning, robust control, and optimal recursive decision-making. The applications span planetary landers and spacecraft swarms.
Explore our research Join the labAbout the lab
The Autonomous Controls Lab (ACL) has moved to UC Berkeley after a decade at the University of Washington. Behçet Açıkmeşe leads the group. The lab connects control theory and optimization with aerospace engineering. Its flight-hardware algorithms are designed for real-time execution and include provable guarantees.
The lab has a theory-to-flight orientation. Lossless convexification and successive convexification, both developed in this research program, have informed planetary landing guidance and reusable rocket flight. The group also maintains open-source solvers and tools used outside the lab.
Research themes
Five threads run through the lab's work. Each combines rigorous theory with algorithms designed for real-time, onboard implementation.
Convex Optimization Algorithms
Custom solvers, including the QOCO quadratic-objective conic optimizer, are built for reliable embedded deployment.
Robust Control
Feedback synthesis that guarantees performance and constraint satisfaction despite uncertainty, disturbances, and model error.
Optimal Recursive Decision-Making
Sequential decision-making under uncertainty, with convex formulations that make optimal policies computationally tractable.
Markov Decision Processes
Density control and policy synthesis for large-scale stochastic systems, including swarm guidance and probabilistic safety.
Recent news
- Skye received the 2025 AIAA Atmospheric Flight Mechanics Best Paper Award for AutoSCvx.
- Sam won the Best Paper Award in the Guidance, Navigation and Control Graduate Student Paper Competition at SciTech 2026.
- Chris passed his PhD candidacy exam. Congratulations!
- Abhi successfully defended his dissertation.