3 papers
cs.RO2026
DODGER: Safety-Guided Reinforcement Learning for Robot Navigation Among Dynamic Obstacles
Sanghyuk Park, Kwanwoo Lee, Taekyung Kim +2
Robots operating in human-centered environments must safely navigate among multiple dynamic obstacles to avoid collisions with people and surrounding infrastructure. Control barrie…
cs.RO2026
Real-Time Dynamics-Based Torque-Sampling MPPI for Compliant and Force Aware Manipulation
Euncheol Im, Taehyun Kim, Yonghwan Oh +2
This study proposes a novel Model Predictive Path Integral (MPPI)-based task-space control framework. The proposed framework explicitly solves rigid-body dynamics within a real-tim…
cs.RO2026
RGB: RL Guided Whole-Body MPPI for Humanoid Control
Yunsoo Seo, Sol Choi, Euncheol Im +2
Humanoid robots require whole-body controllers that are both robust and precise in contact-rich environments. While deep reinforcement learning (RL) achieves robust stability, its…