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The Berkeley Intelligent Control (ICON) lab develops algorithms for autonomous systems to interact with other agents safely and intelligently. Our goal is to enable autonomous systems to become integrated into the fabric of human life and act in the favor of society. To this end, we draw from control theory, game theory, robotics, and machine learning.
news
| Jul 15, 2026 | Our paper titled “Learning Control Policies to Provably Satisfy Hard Affine Constraints for Black-Box Hybrid Dynamical Systems” has been accepted to the Conference on Decision and Control (CDC) 2026! |
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| Jun 23, 2026 | Our PhD student, Hongrui Zhao, successfully defended his dissertation and graduated with his PhD. Congratulations, Dr. Zhao! |
| May 07, 2026 | Our PhD student, Maulik Bhatt, successfully defended his dissertation and graduated with his PhD. Congratulations, Dr. Bhatt! |
| May 04, 2026 | Our PhD student, John Viljoen, passed his qualifying exam and became a PhD candidate. Congratulations John! |
| Apr 29, 2026 | Our paper titled “TACO: Temporal Consensus Optimization for Continual Neural Mapping” has been accepted to the Robotics: Science and Systems (RSS) 2026! |