23 citations · 24 across the 7 of their papers we have counts for
9 papers
WarpMPC: Large-Batch MPC on GPU via ADMM with Unrolled Factorization
Henrik Hose, Se Hwan Jeon, Charles Khazoom +2
This paper introduces numerical optimizations for maximizing throughput on GPU when solving large batches (10,000 to over 100,000) of sequential quadratic programming (SQP) iterati…
Learning Reactive Dexterous Grasping via Hierarchical Task-Space RL Planning and Joint-Space QP Control
Ho Jae Lee, Yonghyeon Lee, Alexander Alexiev +3
In this work, we propose a hybrid hierarchical control framework for reactive dexterous grasping that explicitly decouples high-level spatial intent from low-level joint execution.…
Residual MPC: Blending Reinforcement Learning with GPU-Parallelized Model Predictive Control
Se Hwan Jeon, Ho Jae Lee, Seungwoo Hong +1
Model Predictive Control (MPC) provides interpretable, tunable locomotion controllers grounded in physical models, but its robustness depends on frequent replanning and is limited…
Learning Humanoid Arm Motion via Centroidal Momentum Regularized Multi-Agent Reinforcement Learning
Ho Jae Lee, Se Hwan Jeon, Sangbae Kim
Humans naturally swing their arms during locomotion to regulate whole-body dynamics, reduce angular momentum, and help maintain balance. Inspired by this principle, we present a li…
CusADi: A GPU Parallelization Framework for Symbolic Expressions and Optimal Control
Se Hwan Jeon, Seungwoo Hong, Ho Jae Lee +2
The parallelism afforded by GPUs presents significant advantages in training controllers through reinforcement learning (RL). However, integrating model-based optimization into thi…
Learning Emergent Gaits with Decentralized Phase Oscillators: on the role of Observations, Rewards, and Feedback
Jenny Zhang, Steve Heim, Se Hwan Jeon +1
We present a minimal phase oscillator model for learning quadrupedal locomotion. Each of the four oscillators is coupled only to itself and its corresponding leg through local feed…
Benchmarking Potential Based Rewards for Learning Humanoid Locomotion
Se Hwan Jeon, Steve Heim, Charles Khazoom +1
The main challenge in developing effective reinforcement learning (RL) pipelines is often the design and tuning the reward functions. Well-designed shaping reward can lead to signi…
Practical Detectability for Persistent Lock-Free Data Structures
Kyeongmin Cho, Seungmin Jeon, Jeehoon Kang
Persistent memory (PM) is an emerging class of storage technology that combines the benefits of DRAM and SSD. This characteristic inspires research on persistent objects in PM with…
Real-time Optimal Landing Control of the MIT Mini Cheetah
Se Hwan Jeon, Sangbae Kim, Donghyun Kim
Quadrupedal landing is a complex process involving large impacts, elaborate contact transitions, and is a crucial recovery behavior observed in many biological animals. This work p…