activity
20222024
most citedSynthesize Dexterous Nonprehensile Pregrasp for Ungraspable Objects

16 citations · 27 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2024

In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation

Albert Wu, Dan Kruse

Picking diverse objects in the real world is a fundamental robotics skill. However, many objects in such settings are bulky, heavy, or irregularly shaped, making them ungraspable b…

cs.RO2023★ 16 cited

Synthesize Dexterous Nonprehensile Pregrasp for Ungraspable Objects

Sirui Chen, Albert Wu, C. Karen Liu

Daily objects embedded in a contextual environment are often ungraspable initially. Whether it is a book sandwiched by other books on a fully packed bookshelf or a piece of paper l…

cs.RO2022★ 10 cited

Learning Diverse and Physically Feasible Dexterous Grasps with Generative Model and Bilevel Optimization

Albert Wu, Michelle Guo, C. Karen Liu

To fully utilize the versatility of a multi-fingered dexterous robotic hand for executing diverse object grasps, one must consider the rich physical constraints introduced by hand-…

cs.RO2022

Robust-RRT: Probabilistically-Complete Motion Planning for Uncertain Nonlinear Systems

Albert Wu, Thomas Lew, Kiril Solovey +2

Robust motion planning entails computing a global motion plan that is safe under all possible uncertainty realizations, be it in the system dynamics, the robot's initial position,…

cs.RO2022★ 1 cited

Real-time Model Predictive Control and System Identification Using Differentiable Physics Simulation

Sirui Chen, Keenon Werling, Albert Wu +1

Developing robot controllers in a simulated environment is advantageous but transferring the controllers to the target environment presents challenges, often referred to as the "si…