I am excited by the challenge of creating robots that can operate consistently in complex, unstructured environments.

In my current research, I focus on developing and applying techniques for motion planning, model predictive control (MPC) and time optimal trajectory generation across a spectrum of unique multi-modal robots: A snake robot that can transition between crawling and tumbling modes, aerial vehicles equipped with wheels or legs, and more. 

 

Learning to adapt these methods for each platform has demanded a holistic perspective—balancing control design with an understanding of mechanical constraints, sensor feedback, on-board computational limits, and diverse software, hardware and communication architectures.

 

Combining this with a solid hands-on exposure to robotics perception, including visual-inertial and LiDAR-based SLAM pipelines, state estimation, object detection and segmentation, Neural Radiance Fields (NeRFs), and more, helps me in leading research that covers the full autonomy stack of these unique robots from high level task-based decision making to low level control.​