Teaya Yang

I am a PhD candidate at UC Berkeley advised by Prof. Mark W. Mueller. I am a member of the High Performance Robotics (HiPeR) Lab and affiliated with the Berkeley Artificial Intelligence Research (BAIR) Lab.

I received my B.S. degree in Mechanical Engineering from Cornell University in 2022, where I conducted research under the supervision of Prof. Itai Cohen.

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Research

My research focuses on perception-driven autonomy for uncrewed aerial vehicles (UAVs), with the goal of enabling reliable operation at scale in complex, GPS-denied environments. Working at the intersection of perception, state estimation, and motion planning, I develop methods that allow UAVs to reason about their environment and navigate using onboard sensing. My current work explores information-theoretic approaches to perception-aware navigation, alongside field robotics applications in agriculture and infrastructure inspection and maintenance.

I'm always happy to connect and collaborate. If you're interested in my work, feel free to reach out!

An occlusion-aware motion planning framework for avoiding potential collisions with agents hidden behind obstacles.

An autonomous system that applies protective coatings to solar panels using onboard perception and control for close-proximity flight.

A multi-UAV trajectory planning framework that incorporates vision-based estimator uncertainty through shared feature alignment and perception-aware rewards.

An autonomous system for fruit counting through RGB images with a focus on through-the-canopy data collection.

A simulator for UAV navigation in agricultural environments with built-in support for visual-inertial odometry.

A collision-aware path recovery method for high-speed tensegrity drones using binary contact sensing and vector-field-based navigation.

A novel design paradigm for multistate machines where state transitions are organized by bifurcations of equilibria.

This website is adapted from Jon Barron. Last updated: Sep, 2026