One of the main research focuses in my PhD was developing a more robust balance controller for the Cornell Ranger walking robot . I developed a controller architecture for the robot that allowed for automated controller design, both in simulation and in hardware. The gains for the balance controller were initially computed using large-scale optimization in simulation. The simulation was designed to include a wide range of disturbances, so that we could usually transfer controllers directly from simulation to the real robot. Once on the robot, the balance controller gains were fine-tuned using optimization that was running in real-time on the robot.
I spent much of my time at Cornell learning trajectory optimization and coding up my own solvers. I found learning about the subject fascinating, so I developed a set of tutorials for trajectory optimization, including a long paper that is going to be published in SIAM in December 2017.
Conference paper for ICRA 2015. The key contribution is a way of posing and solving the following constrained optimization problem: "Find a controller that can regulate walking speed while preventing all falls, given any (bounded) disturbance."
I took my A exam in August 2014. My proposal was on the topic of 'Heirarchical Biped Control'. The idea is to do step planning on a reduced model of the robot, which is then used to help generate the motor commands on the full model. In addition to my presentation, I submitted three written reports.
For my qualifying exam (January 2012) I presented a simulation of a tractor trailer truck driving backwards along a curving road. It had partial sensing of its state using noisy sensors, and control of the steering angle and travel speed (both of which were bounded). State estimation was done using an extended Kalman filter (EKF). Control was done by using a discrete linear quadratic regulator (dLQR), on the linearized system (about the current state estimate).
My undergraduate thesis project at Tufts University was designing, fabricating, and testing a new type of surgical bone saw. At the conclusion of the project I submitted provisional patent for my saw design and published the experimental results in the ASME Journal of Medical Devices. I was also worked on two conference papers - one for my saw, and one for a saw designed by another student.
Research advisor: Tom James
In my last year of undergrad, I worked as a research assistant in the Non-Newtonian Fluids lab at MIT, along with Tim Lannin and Will Langford. Our goal was to design and implement a non-linear tracking controller on their Filament Stretching Extensional Rheometer (FiSER) and to redesign the LabVIEW program that ran the experiments.
FiSER characterizes fluids by rapidly stretching them, and measuring both the axial force on the fluid and the diameter of the sample in real time. The original experiments were done by using open-loop velocity profiles for the two measurement stages of the device. We implemented a controller that adjusted the speed of the stages in real-time to track a desired diameter profile in the specimen. This was challenging because the reference trajectories were all exponential, requiring the use of non-linear control techniques. The data acquisition, control, and estimation code were written in LabVIEW and compiled to a National Instruments cRIO and FPGA.
Research advisors: Chris Rogers and Gareth McKinley.
As an freshman at Tufts University, I took a chemistry course, which was designed to teach chemistry by attempting to answer the question: "Is hydrogen the fuel of the future?". My final report for the class was included in supplement of the paper that my professor wrote about the course.