Teaya Yang

I am a PhD student majoring in Controls 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 undergraduate research under the supervision of Prof. Itai Cohen.

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Research

I'm broadly interested in robotics, controls, dynamical systems, and computer vision, with a focus on advancing vision-based capabilities of unmanned aerial vehicles (UAVs). My work spans simulation and real-world applications, exploiting the visual advantage of UAVs to enable large-scale data collection in complex environments.

I am currently exploring novel strategies for navigation, mapping, and state estimation in UAVs, with a particular focus on vision-based methods. As part of this effort, I am also developing a simulation framework to support rapid testing and evaluation. I’m additionally interested in multi-agent systems, where collaboration among UAVs can improve navigation accuracy and robustness, enabling deployment in challenging environments.

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

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 simulator for UAVs with a focus on agricultural applications.

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: May, 2025