1 citations · 1 across the 10 of their papers we have counts for
10 papers
SOLO: Stable Omni-terrain Long-Horizon Perceptive Humanoid Locomotion
Pihai Sun, Gang Han, Jingkai Sun +17
Humans traverse complex terrain over long distances without losing balance, whereas perceptive humanoid policies become fragile as perception and control errors accumulate. We pres…
MeshMimic: Geometry-Aware Humanoid Motion Learning through 3D Scene Reconstruction
Qiang Zhang, Jiahao Ma, Peiran Liu +20
Humanoid motion control has witnessed significant breakthroughs in recent years, with deep reinforcement learning (RL) emerging as a primary catalyst for achieving complex, human-l…
Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition
Jiahang Cao, Yize Huang, Hanzhong Guo +15
Diffusion-based models for robotic control, including vision-language-action (VLA) and vision-action (VA) policies, have demonstrated significant capabilities. Yet their advancemen…
Humanoid Occupancy: Enabling A Generalized Multimodal Occupancy Perception System on Humanoid Robots
Wei Cui, Haoyu Wang, Wenkang Qin +19
Humanoid robot technology is advancing rapidly, with manufacturers introducing diverse heterogeneous visual perception modules tailored to specific scenarios. Among various percept…
Occupancy World Model for Robots
Zhang Zhang, Qiang Zhang, Wei Cui +12
Understanding and forecasting the scene evolutions deeply affect the exploration and decision of embodied agents. While traditional methods simulate scene evolutions through trajec…
Modality-Composable Diffusion Policy via Inference-Time Distribution-level Composition
Jiahang Cao, Qiang Zhang, Hanzhong Guo +3
Diffusion Policy (DP) has attracted significant attention as an effective method for policy representation due to its capacity to model multi-distribution dynamics. However, curren…
Spiking Neural Network as Adaptive Event Stream Slicer
Jiahang Cao, Mingyuan Sun, Ziqing Wang +4
Event-based cameras are attracting significant interest as they provide rich edge information, high dynamic range, and high temporal resolution. Many state-of-the-art event-based a…
Mamba Policy: Towards Efficient 3D Diffusion Policy with Hybrid Selective State Models
Jiahang Cao, Qiang Zhang, Jingkai Sun +11
Diffusion models have been widely employed in the field of 3D manipulation due to their efficient capability to learn distributions, allowing for precise prediction of action traje…
Mamba as Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning
Jiahang Cao, Qiang Zhang, Ziqing Wang +8
Sequential modeling has demonstrated remarkable capabilities in offline reinforcement learning (RL), with Decision Transformer (DT) being one of the most notable representatives, a…
Spiking Denoising Diffusion Probabilistic Models
Jiahang Cao, Ziqing Wang, Hanzhong Guo +3
Spiking neural networks (SNNs) have ultra-low energy consumption and high biological plausibility due to their binary and bio-driven nature compared with artificial neural networks…