Robots that touch, grasp, and assemble.
Most robots can move; few can manipulate. This group studies contact-rich control — the tactile sensing, force control, and dexterous, often bimanual coordination needed to handle real objects and finish physical tasks to precision and tolerance.
How this group works.
The methods and commitments that define the lab's approach to the problem.
Beyond pick-and-place
Policies for insertion, assembly, and tool use — tasks defined by forces and tolerances, not just positions.
Feeling, not just seeing
Touch as a first-class sensor: slip detection, contact geometry, and force feedback closing the loop where vision can't reach.
Two hands, one task
Coordinated control for what a single manipulator can't do alone — bracing, reorienting, and handing off.
Hands worth controlling
Co-designing grippers and actuation with the policies that drive them, so capability isn't capped by the mechanism.
Open problems we're pursuing.
The questions the lab is taking on now — each a gap between what works in a demo and what works in the world.
Force-controlled assembly
Policies that hit tight tolerances under uncertainty — the gap between a demo and a production cell.
Tactile-driven policy learning
How much does touch add over vision alone, and how do you train with it at scale?
Manipulation sim-to-real
Contact dynamics are the hardest thing to simulate faithfully — how far does randomization actually carry?
Lead this group, or join it.
Step into the principal-investigator role through the Physical AI Investigator Program — an independent appointment with PI authority — or join the group as a research intern.
Physical AI Investigator Program
An independent investigator appointment and PI authority to lead a research line in this group — built to position you for early-career funding.
Research in this group can spin out into a company — explore Launch →