YCB Object and Model Set Project on the cover of 2017 Yale Engineering Magazine

"Grasping the future of robotics"

Aaron Dollar and I gave an interview for the annual Yale Engineering magazine about the Yale-CMU-Berkeley Object and Model Set Project. The article and the full magazine are available below.


Vision-based MPC improves in-hand manipulation efficiency

Model Predictive Control reduces the effects of modeling inaccuracies

Our latest results show that high performance in-hand manipulation can be achieved even with very rough process models. Combining visual feedback, system compliance and model predictive control framework allows us to minimize the effect of modeling inaccuracies and maintain efficiency. Our approach also removes the need for joint encoders and force sensors.


In the face of modeling inaccuracies, MPC makes the system follow a shorter path (green line) comparing to the traditional IBVS controller (red line).

"A forgotten right of citizens: Technology"

A discussion on how to increase citizen participation in technological development

My article is published in a Turkish political magazine Ayrinti Dergi's special issue on citizenship (only available in Turkish).

Model-free active vision for robotics

An approach for viewpoint optimization using extremum seeking

We propose a new methodology for optimizing the viewpoint of a robot's vision sensor without the need of an explicit objective function. The article will be available soon. Sneak peek results are available here.