4 papers
ADP: Adversarial Dynamics Priors for Physically Grounded Humanoid Locomotion
Seokju Lee, Jeongtae Lee, Jeonghyeok Lim +6
In this paper, we propose Adversarial Dynamics Priors (ADP) for perturbation-resilient humanoid locomotion control. Existing motion prior-based methods induce natural motion styles…
RAY-TOLD: Ray-Based Latent Dynamics for Dense Dynamic Obstacle Avoidance with TDMPC
Seungho Han, Seokju Lee, Jeonguk Kang
Dense, dynamic crowds pose a persistent challenge for autonomous mobile robots. Purely reactive planning methods, such as Model Predictive Path Integral (MPPI) control, often fail…
Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies
Pokuang Zhou, Yuhao Zhou, Quan Khanh Luu +7
Quadrupedal loco-manipulation is commonly built on visual perception and proprioception. Yet reliable contact-rich manipulation remains difficult: vision and proprioception alone c…
EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation
Zhiyuan Zhang, Aditya Mohan, Seungho Han +3
Robotic imitation learning has achieved impressive success in learning complex manipulation behaviors from demonstrations. However, many existing robot learning methods do not expl…