2 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
HJCD-IK: GPU-Accelerated Inverse Kinematics through Batched Hybrid Jacobian Coordinate Descent
Cael Yasutake, Andrew H. Liu, Zachary Kingston +1
Inverse Kinematics (IK) is a core problem in robotics, in which joint configurations are found to achieve a (collision-free) desired end-effector pose. Modern IK solvers face a fun…
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…
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…
Code Generation and Conic Constraints for Model-Predictive Control on Microcontrollers with Conic-TinyMPC
Ishaan Mahajan, Khai Nguyen, Sam Schoedel +4
Model-predictive control (MPC) is a state-of-the-art control method for constrained robotic systems, yet deployment on resource-limited hardware remains difficult. This challenge i…