Robotics PhD at Stanford University making robots that perceive through touch

I research how robots can use the sense of touch to execute tasks more effectively in unstructured settings such as our homes. I develop robots equipped with tactile sensing that can safely and quickly make contact with objects and leverage this contact information for grasping or exploration of objects.

I am part of the Biomimetric and Dexterous Manipulation Lab, advised by Prof. Mark Cutkosky. Prior to my PhD, I was a Robotics System Engineer at Flexiv Robotics Inc. developing the mechatronics and controls of a 7 degrees-of-freedom torque-controlled robot arm for industrial task automation. I completed my undergraduate in Electrical Engineering and Computer Science at UC Berkeley with a focus in mechatronics and signals and systems.

Google Scholar

A man smiling, black hair, wearing jacket and blue lake in background.

Latest Research

A GIF image showing a robot gripper moving inside a cabinet and making contact with four spice jars quickly, and then grasping one of the spice jars.

Exploratory Hand: Leveraging Safe Contact to Facilitate Manipulation in Cluttered Spaces

Michael A. Lin, Rachel Thomasson, Gabriela Uribe, Hojung Choi and Mark R. Cutkosky

We present a new gripper and exploration approach that uses an exploratory finger with very low reflected inertia for probing and grasping objects quickly and safely in unstructured environments. Equipped with sensing and force control, the gripper allows a robot to leverage contact information to accurately estimate object location through a particle filtering algorithm and also grasp objects with location uncertainty based on a contact-first approach. This publication is still under review so it is not yet available.

A robot arm with a custom designed 2-DOF wrist that wears a white sleeve with soft pneumatic sensors. The robot is reaching into a fridge drawer to retrieve a pear.

A Stretchable Tactile Sleeve for Reaching into Cluttered Spaces

Alexander M. Gruebele, Michael A. Lin, Dane Brouwer, Shenli Yuan, Andrew Zerbe and Mark R. Cutkosky

A highly conformable stretchable sensory skin made entirely of soft components. The skin uses pneumatic taxels and stretchable channels to conduct pressure signals to off-board MEMs pressure sensors. The skin is able to resolve forces down to 0.01N and responds to vibrations up to 200 Hz. We apply the skin to a 2 degree-of-freedom robotic wrist with intersecting axes for manipulation in constrained spaces, and show that it has sufficient sensitivity and bandwidth to detect the onset of sliding as the robot contacts objects. We demonstrate the skin in object acquisition tasks in a tightly constrained environment for which extraneous contacts are unavoidable.

Skills Highlight

Python / C++ / C Language / PyTorch / Git / Linux
ROS / PyBullet / RBDL (Rigid Body Dynamics Library)
Embedded Systems
State Machines / SPI / UART / EtherCAT / BLE
Brushless motor control / Circuit design / CAD modeling