collaborators

5 papers

cs.RO2026

Projection-Retraction MPPI: Exact Constraint-Manifold Control for Manipulators

Seulchan Lee, Leesai Park, Minhyeong Kang +1

Model Predictive Path Integral (MPPI) control is widely used in manipulation for its gradient-free, parallel handling of non-convex costs. Manipulation tasks, however, often impose…

cs.RO2026

GRACE: Gradient-Free Robot Action Generation via Combined Diffusion-MPPI Posterior Mean Estimation

Leesai Park, Jiho HOng, Sanghyun Kim

Diffusion policies generate multimodal robot action sequences from demonstrations, but steering them toward deployment-time constraints typically relies on differentiable guidance…

cs.RO2026

Manifold-Constrained MPPI: Real-Time Sampling-Based Control Under Hard Constraints

Seulchan Lee, Sanghyun Kim

Sampling-based model predictive control methods, such as Model Predictive Path Integral (MPPI), offer derivative-free optimization and robustness in complex robotic systems. Howeve…

cs.RO2026

BAT: Balancing Agility and Stability via Online Policy Switching for Long-Horizon Whole-Body Humanoid Control

Donghoon Baek, Sang-Hun Kim, Sehoon Ha

Despite recent advances in control, reinforcement learning, and imitation learning, developing a unified framework that can achieve agile, precise, and robust whole-body behaviors,…

cs.RO2025

CSC-MPPI: A Novel Constrained MPPI Framework with DBSCAN for Reliable Obstacle Avoidance

Leesai Park, Keunwoo Jang, Sanghyun Kim

This paper proposes Constrained Sampling Cluster Model Predictive Path Integral (CSC-MPPI), a novel constrained formulation of MPPI designed to enhance trajectory optimization whil…