17 citations · 43 across the 15 of their papers we have counts for
6 papers · 1 filter
pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation
Brian Plancher
GPU acceleration is now routine across robotics, but cloud-hosted GPU continuous integration (CI) runners are expensive, resulting in severe under-testing of GPU-accelerated code.…
GLASS: Architecture-Tuned, Composable, Device-Side Linear Algebra for Edge Robotics and Beyond
Brian Plancher
GPU robotics lacks the reusable numerical infrastructure of mature CPU stacks, instead relying on compiler frameworks that introduce overhead or repeatedly reimplementing numerical…
MPC-Injection: Biasing Off-Policy Locomotion RL Toward Controller-Induced Behavior Basins
Roy Xing, Seyoung Ree, Brian Plancher
Reinforcement learning (RL) for locomotion frequently converges to locally optimal but undeployable behaviors, such as vibrating limbs or scooting on the torso, that maximize retur…
Parallel Dynamic Programming for Conic Linear Quadratic Control
Luyao Zhang, Gabriel Bravo-Palacios, Brian Plancher +1
Linear Quadratic (LQ) control problems are at the heart of linear control theory and Model Predictive Control (MPC). While performant, standard approaches to solving such problems…
TurboMPC: Fast, Scalable, and Differentiable Model Predictive Control on the GPU
Gabriel Bravo-Palacios, Jianghan Zhang, Zachary Pestrikov +2
Robotics increasingly relies on GPUs for parallel simulation, large-scale learning, and neural-network inference. For model predictive control (MPC) to scale with this paradigm, so…
ASCII Art Turns LLMs into VLA Controllers
Yitao Jiang, Roy Xing, Luyang Zhao +3
Vision--Language--Action (VLA) controllers are often built by extending vision--language models (VLMs) with action supervision, relying on multimodal backbones with large data and…