4 citations · 4 across the 9 of their papers we have counts for
6 papers · 1 filter
Humanoid Horizon: Extending Task Horizon in Whole-Body Loco-Manipulation via Parallel Training, Dynamic Starting, and Reward Gating
Haozhuo Zhang, Qiang Zhang, Jian Tang +4
Cluttered indoor environments, where large and heavy objects are scattered across diverse surfaces, require humanoid robots to sequentially navigate, grasp, transport, and accurate…
PROMO: Preference-conditioned Multi-Objective Reinforcement Learning for Quadrupedal Robots
Amr Mousa, Rifny Rachman, Neil Karavis +2
Quadrupedal locomotion requires balancing conflicting objectives such as command tracking, stability, and energy efficiency, yet conventional reinforcement learning (RL) hardcodes…
CoCoNav: Conformal Control for Safe Robot Navigation in Crowds
Cheng Guo, Mingzhe Ni, Zheng Liang +5
Safe and efficient robot navigation in crowds requires anticipating pedestrian motion despite uncertain and potentially shifting prediction errors. Existing reactive methods can pr…
PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Control
Haozhuo Zhang, Michele Caprio, Jing Shao +4
We present PoseDiff, a conditional diffusion model that unifies robot state estimation and control within a single framework. At its core, PoseDiff maps raw visual observations int…
LHM-Humanoid: Long-Horizon Human Motion Control for Continuous Object Transport in Cluttered Scenes
Haozhuo Zhang, Jingkai Sun, Michele Caprio +5
Physics-based human motion control can make a simulated character walk, sit, and manipulate objects with high physical realism. Almost always, though, this happens in short, isolat…
TAR: Teacher-Aligned Representations via Contrastive Learning for Quadrupedal Locomotion
Amr Mousa, Neil Karavis, Michele Caprio +2
Quadrupedal locomotion via Reinforcement Learning (RL) is commonly addressed using the teacher-student paradigm, where a privileged teacher guides a proprioceptive student policy.…