3 citations · 8 across the 37 of their papers we have counts for
21 papers · 1 filter
Encoded but Not in Control: Revealing the Grounding Gap in Vision-Language Robot Policies
Shaohan Jiang, Jiahang Cao, Qiduo He +9
Instruction following is central to language-conditioned robot policies: language should determine what to do when the same scene permits multiple valid actions. Yet successful exe…
Vela: Scaling Vision-Language-Action Models with Adaptive Action Curve Parametrization
Yifan Li, Jiaxu Wang, Dongming Wu +4
Most vision-language-action models represent future motion as fixed-rate action chunks, tying temporal resolution and prediction horizon to a fixed output budget. This pointwise re…
AR-WAM: A Visual-Conditioned Agent-Ready World Action Model for Robotic Manipulation
Yicheng Jiang, Zesen Gan, Xiaobo Wang +8
As AI agents become increasingly capable, agent-driven robotic control is emerging as a compelling paradigm. However, prevailing vision-language-action (VLA) models and world actio…
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…
-VLA: a Hierarchical Robot Foundation Model with World-Model-Guided Test-Time Computation
Xiaowei Cai, Yunuo Cai, Bingao Chen +36
Long-horizon robot manipulation requires a robot to both execute individual skills reliably and sequence them coherently over extended tasks. Most hierarchical vision-language-acti…
-WM: A Unified Video-Action World Model for Robotic Manipulation
Pengfei Zhou, Shengcong Chen, Di Chen +17
Robotic manipulation requires models that generate executable actions while anticipating and evaluating their future consequences before physical execution. We present -World…
Learning Structural Latent Points for Efficient Visual Representations in Robotic Manipulation
Yicheng Jiang, Jiaxu Wang, Junhao He +8
Current 3D-aware pretraining methods for embodied perception and manipulation are largely built on differentiable rendering frameworks, producing either fully implicit neural field…
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…
DPL: Depth-only Perceptive Humanoid Locomotion via Realistic Depth Synthesis and Cross-Attention Terrain Reconstruction
Jingkai Sun, Gang Han, Pihai Sun +5
Recent advancements in legged robot perceptive locomotion have shown promising progress. However, terrain-aware humanoid locomotion remains largely constrained to two paradigms: de…
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…
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…
EmbodiedVSR: Dynamic Scene Graph-Guided Chain-of-Thought Reasoning for Visual Spatial Tasks
Yi Zhang, Qiang Zhang, Xiaozhu Ju +13
While multimodal large language models (MLLMs) have made groundbreaking progress in embodied intelligence, they still face significant challenges in spatial reasoning for complex l…
HumanoidPano: Hybrid Spherical Panoramic-LiDAR Cross-Modal Perception for Humanoid Robots
Qiang Zhang, Zhang Zhang, Wei Cui +13
The perceptual system design for humanoid robots poses unique challenges due to inherent structural constraints that cause severe self-occlusion and limited field-of-view (FOV). We…
LiPS: Large-Scale Humanoid Robot Reinforcement Learning with Parallel-Series Structures
Qiang Zhang, Gang Han, Jingkai Sun +7
In recent years, research on humanoid robots has garnered significant attention, particularly in reinforcement learning based control algorithms, which have achieved major breakthr…
Trinity: A Modular Humanoid Robot AI System
Jingkai Sun, Qiang Zhang, Gang Han +7
In recent years, research on humanoid robots has garnered increasing attention. With breakthroughs in various types of artificial intelligence algorithms, embodied intelligence, ex…
Distillation-PPO: A Novel Two-Stage Reinforcement Learning Framework for Humanoid Robot Perceptive Locomotion
Qiang Zhang, Gang Han, Jingkai Sun +6
In recent years, humanoid robots have garnered significant attention from both academia and industry due to their high adaptability to environments and human-like characteristics.…
E2H: A Two-Stage Non-Invasive Neural Signal Driven Humanoid Robotic Whole-Body Control Framework
Yiqun Duan, Qiang Zhang, Jinzhao Zhou +9
Recent advancements in humanoid robotics, including the integration of hierarchical reinforcement learning-based control and the utilization of LLM planning, have significantly enh…
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…
Query-based Semantic Gaussian Field for Scene Representation in Reinforcement Learning
Jiaxu Wang, Ziyi Zhang, Qiang Zhang +5
Latent scene representation plays a significant role in training reinforcement learning (RL) agents. To obtain good latent vectors describing the scenes, recent works incorporate t…
Physical Priors Augmented Event-Based 3D Reconstruction
Jiaxu Wang, Junhao He, Ziyi Zhang +1
3D neural implicit representations play a significant component in many robotic applications. However, reconstructing neural radiance fields (NeRF) from realistic event data remain…