3 citations · 11 across the 32 of their papers we have counts for
23 papers · 1 filter
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…
VAIC: Vision-Guided Humanoid Agile Object Interaction Control via Decoupled Commands
Dongting Li, Qianyang Wu, Xingyu Chen +9
Humanoid robots hold immense potential for real-world assistance, yet agile interaction with objects in unstructured environments demands tightly coupled whole-body coordination. D…
RobotPan: A 360 Surround-View Robotic Vision System for Embodied Perception
Jiahao Ma, Qiang Zhang, Peiran Liu +11
Surround-view perception is increasingly important for robotic navigation and loco-manipulation, especially in human-in-the-loop settings such as teleoperation, data collection, an…
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…
TopoNav: Topological Graphs as a Key Enabler for Advanced Object Navigation
Peiran Liu, Qiang Zhang, Daojie Peng +6
Object Navigation (ObjectNav) has made great progress with large language models (LLMs), but still faces challenges in memory management, especially in long-horizon tasks and dynam…
RoboOcc: Enhancing the Geometric and Semantic Scene Understanding for Robots
Zhang Zhang, Qiang Zhang, Wei Cui +7
3D occupancy prediction enables the robots to obtain spatial fine-grained geometry and semantics of the surrounding scene, and has become an essential task for embodied perception.…
ES-Parkour: Advanced Robot Parkour with Bio-inspired Event Camera and Spiking Neural Network
Qiang Zhang, Jiahang Cao, Jingkai Sun +5
In recent years, quadruped robotics has advanced significantly, particularly in perception and motion control via reinforcement learning, enabling complex motions in challenging en…
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…
Multi-Floor Zero-Shot Object Navigation Policy
Lingfeng Zhang, Hao Wang, Erjia Xiao +4
Object navigation in multi-floor environments presents a formidable challenge in robotics, requiring sophisticated spatial reasoning and adaptive exploration strategies. Traditiona…
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…
Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs
Yiqun Duan, Qiang Zhang, Renjing Xu
The utilization of Large Language Models (LLMs) within the realm of reinforcement learning, particularly as planners, has garnered a significant degree of attention in recent schol…
TriHelper: Zero-Shot Object Navigation with Dynamic Assistance
Lingfeng Zhang, Qiang Zhang, Hao Wang +4
Navigating toward specific objects in unknown environments without additional training, known as Zero-Shot object navigation, poses a significant challenge in the field of robotics…
Whole-body Humanoid Robot Locomotion with Human Reference
Qiang Zhang, Peter Cui, David Yan +8
Recently, humanoid robots have made significant advances in their ability to perform challenging tasks due to the deployment of Reinforcement Learning (RL), however, the inherent c…
Fully Spiking Neural Network for Legged Robots
Xiaoyang Jiang, Qiang Zhang, Jingkai Sun +3
Recent advancements in legged robots using deep reinforcement learning have led to significant progress. Quadruped robots can perform complex tasks in challenging environments, whi…
Prompt, Plan, Perform: LLM-based Humanoid Control via Quantized Imitation Learning
Jingkai Sun, Qiang Zhang, Yiqun Duan +3
In recent years, reinforcement learning and imitation learning have shown great potential for controlling humanoid robots' motion. However, these methods typically create simulatio…