Dynamic Autonomy and Intelligent Robotics Lab
170B Towne Building, 220 S. 33rd Street, Philadelphia PA, 19104
Welcome to the Dynamic Autonomy and Intelligent Robotics (DAIR) Lab!
Our research centers on planning, control, and formal analysis of robots as they interact with the world. Whether a robot is assisting within the home, or operating in a manufacturing plant, the fundamental promise of robotics requires touching and affecting a complex environment in a safe and controlled fashion. We are focused on developing computationally tractable algorithms which enable robots to operate both dynamically and safely as they quickly maneuver through and interact with their environments.
Right now, we are particularly interested in understanding the interplay between the non-smooth dynamics of contact and numerical optimization, and then testing these techniques on both legged robots and robotic manipulation.
We are proud to be a group within the Penn Engineering GRASP Lab.
Recent Updates
| Oct 21, 2021 |
We’re excited that the paper “Stabilization of Complementarity Systems via Contact-Aware Controllers,” led by Alp Aydinoglu, has been accepted for publication in IEEE Transactions on Robotics (TRO). In it, we solve bilinear matrix inequalities to synthesize control policies that explicitly use measured state and force for feedback. Check out the video where the controller stabilizies a cart-pole that slams into nearby walls!
https://arxiv.org/abs/2008.02104 |
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| Oct 20, 2021 |
Michael gave the Robotics Seminar at MIT not too long ago. The talk was recorded and is publically available.
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| Oct 14, 2021 | How well do modern robotics simulators reproduce impact dynamics? How important are appropriately tuned contact parameters for physical realism? We compared simulated trajectories against real impact data from a cube toss and Penn Cassie jumping (or more accurately, landing). Simulators faithfully capture near rigid impacts while struggling with elasticity. While accuracy in reproducing cube toss data is largely insensitive to contact parameters if the parameters are stiff enough, correct stiffness and damping are necessary for accurately reproducing Cassie trajectories. https://arxiv.org/abs/2110.00541 |
| Oct 13, 2021 | The lab has a new website. We’ve copied over some of our more recent news posts, but are largely starting fresh. Check it out! |
| Oct 1, 2021 | When a robot interacts with the world, inevitably it will touch the wrong thing or slip instead of sticking. How should feedback work when the contact mode is changing? Linearization is not useful and hybrid (MIQP) problems cannot be solved in real-time. I’ve been thinking about this problem since the start of my Ph.D., and we’ve finally made some real progress! An ADMM algorithm, which we call Consensus Complementarity Control (C3), jointly optimizes over trajectory and contact mode for real-time MPC. https://arxiv.org/abs/2109.07076 |
Lab Wiki (private)