1 citations · 1 across the 12 of their papers we have counts for
12 papers
Handroid: Bridging Dexterous Hand and Humanoid
Ruogu Li, Chenyang Ma, Sikai Li +6
Dexterous hands and humanoid robots are typically developed as distinct embodiments: the former enable contact-rich manipulation at the object scale, whereas the latter provide mob…
CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models
He Liang, Chenyang Ma, Yiming Zhang +4
Existing 3D scene-grounded Large Language Models (3D-LLMs) focus on answering questions grounded in simplified single-room 3D scenes, lacking the ability to reason over real-world…
DexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation
Yunchao Yao, Zhuxiu Xu, Tianqi Zhang +12
Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across diverse interaction modes, sen…
Current as Touch: Proprioceptive Contact Feedback for Compliant Dexterous Manipulation
Chenyang Ma, Yunchao Yao, Zhenyu Wei +3
Compliance is essential for dexterous manipulation, yet existing solutions often rely on external tactile or force sensors that are costly, fragile, and difficult to deploy on low-…
FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model
Chenyang Ma, Yue Yang, Radu Corcodel +4
Current work on robot furniture assembly mostly focuses on toy-scale settings or single-arm manipulation. We introduce FurnitureVLA, the first systematic study of real-scale bimanu…
UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation
Jiahang Tu, Fengyu Yang, Chenyang Ma +8
Unified multimodal models (UMMs) have shown great promise in integrating understanding and generation across diverse modalities. However, existing research rarely extends this para…
PACT: Proactive Asking for Continual Task Assistance in Human-Robot Collaboration
Chengbo He, Sheng Li, Chenyang Ma +6
Robotic assistants in long-term human-robot collaboration need to assist users under partial observations while leveraging cross-day interaction history. However, human traits and…
EmbeWebAgent: Embedding Web Agents into Any Customized UI
Chenyang Ma, Clyde Fare, Matthew Wilson +1
Most web agents operate at the human interface level, observing screenshots or raw DOM trees without application-level access, which limits robustness and action expressiveness. In…
CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding
Chenyang Ma, Kai Lu, Guangyu Yang +6
Current work on robot failure detection and correction typically operates in a post hoc manner, analyzing errors and applying corrections only after failures occur. This work intro…
COOPERA: Continual Open-Ended Human-Robot Assistance
Chenyang Ma, Kai Lu, Ruta Desai +3
To understand and collaborate with humans, robots must account for individual human traits, habits, and activities over time. However, most robotic assistants lack these abilities,…
SpatialPIN: Enhancing Spatial Reasoning Capabilities of Vision-Language Models through Prompting and Interacting 3D Priors
Chenyang Ma, Kai Lu, Ta-Ying Cheng +2
Current state-of-the-art spatial reasoning-enhanced VLMs are trained to excel at spatial visual question answering (VQA). However, we believe that higher-level 3D-aware tasks, such…
Pre-Training LiDAR-Based 3D Object Detectors Through Colorization
Tai-Yu Pan, Chenyang Ma, Tianle Chen +7
Accurate 3D object detection and understanding for self-driving cars heavily relies on LiDAR point clouds, necessitating large amounts of labeled data to train. In this work, we in…