Projects

Push Anything: Single- and Multi-Object Pushing from First Sight with Contact-Implicit MPC

Push Anything: Single- and Multi-Object Pushing from First Sight with Contact-Implicit MPC

Non-prehensile manipulation of diverse objects remains a core challenge in robotics, driven by unknown physical properties and the complexity of contact-rich interactions. Recent advances in contact-implicit model predictive control (CI-MPC), with contact reasoning embedded within the trajectory optimization, have shown promise in tackling the task efficiently and robustly, yet demonstrations have been limited to narrowly-curated examples. In this work, we showcase the broader capabilities of CI-MPC through precise planar pushing tasks over a wide range of object geometries, including multi-object domains. These scenarios demand reasoning over numerous inter-object and object-environment contacts to strategically manipulate and de-clutter the environment, challenges that were intractable for prior CI-MPC methods. To achieve this, we introduce Consensus Complementarity Control Plus (C3+), an enhanced CI-MPC algorithm integrated into a complete pipeline spanning object scanning, mesh reconstruction, and hardware execution. Compared to its predecessor C3 , C3+ achieves substantially faster solve times, enabling real-time performance even in multi-object pushing tasks. On hardware, our system achieves overall 98% success rate across 33 objects, reaching pose goals within tight tolerances. The average time-to-goal is approximately 0.5, 1.6, 3.2, and 5.3 minutes for 1-, 2-, 3-, and 4-object tasks, respectively.

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Brian Acosta

Robotics Master's '24; PhD, MEAM '25 - Robotics/AI Engineer, Figure


Michael Posa

Assistant Professor, MEAM


Thomas Felix

Robotics MSE


Xuan Hien Bui

Robotics Master's '24; PhD, MEAM


Yufeiyang Gao

Robotics MSE


Push Anything: Single- and Multi-Object Pushing from First Sight with Contact-Implicit MPC