8 citations · 9 across the 7 of their papers we have counts for
7 papers
Complementarity by Construction: A Lie-Group Approach to Solving Quadratic Programs with Linear Complementarity Constraints
Arun L. Bishop, Micah I. Reich, Zachary Manchester
Many problems in robotics require reasoning over a mix of continuous dynamics and discrete events, such as making and breaking contact in manipulation and locomotion. These problem…
How to Train Your Latent Control Barrier Function: Smooth Safety Filtering Under Hard-to-Model Constraints
Kensuke Nakamura, Arun L. Bishop, Steven Man +3
Latent safety filters extend Hamilton-Jacobi (HJ) reachability to operate on latent state representations and dynamics learned directly from high-dimensional observations, enabling…
The Surprising Effectiveness of Linear Models for Whole-Body Model-Predictive Control
Arun L. Bishop, Juan Alvarez-Padilla, Sam Schoedel +8
When do locomotion controllers require reasoning about nonlinearities? In this work, we show that a whole-body model-predictive controller using a simple linear time-invariant appr…
Wallbounce : Push wall to navigate with Contact-Implicit MPC
Xiaohan Liu, Cunxi Dai, John Z. Zhang +3
In this work, we introduce a framework that enables highly maneuverable locomotion using non-periodic contacts. This task is challenging for traditional optimization and planning m…
ReLU-QP: A GPU-Accelerated Quadratic Programming Solver for Model-Predictive Control
Arun L. Bishop, John Z. Zhang, Swaminathan Gurumurthy +2
We present ReLU-QP, a GPU-accelerated solver for quadratic programs (QPs) that is capable of solving high-dimensional control problems at real-time rates. ReLU-QP is derived by exa…
SLoMo: A General System for Legged Robot Motion Imitation from Casual Videos
John Z. Zhang, Shuo Yang, Gengshan Yang +3
We present SLoMo: a first-of-its-kind framework for transferring skilled motions from casually captured "in the wild" video footage of humans and animals to legged robots. SLoMo wo…
Fast Contact-Implicit Model-Predictive Control
Simon Le Cleac'h, Taylor Howell, Shuo Yang +5
We present a general approach for controlling robotic systems that make and break contact with their environments. Contact-implicit model predictive control (CI-MPC) generalizes li…