10 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…
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-…
DexCompose: Reusing Dexterous Policies for Multi-Task Manipulation with a Single Hand
Dihong Huang, Zhenyu Wei, Zhuxiu Xu +3
Dexterous manipulation policies can solve individual skills, but composing them to perform multiple tasks with a single hand remains challenging. Adding a new task on top of an exi…
CoorDex: Coordinating Body and Hand Priors for Continuous Dexterous Humanoid Loco-Manipulation
Sikai Li, Shuning Li, Zhenyu Wei +3
Humanoid loco-manipulation is often simplified into a stop-and-go process: walking to an object, stopping to manipulate it, and then resuming locomotion. It also commonly relies on…
Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation
Arthur Jakobsson, Abhinav Mahajan, Karthik Pullalarevu +6
Many robotic tasks are unforgiving; a single mistake in a dynamic throw can lead to unacceptable delays or unrecoverable failure. We introduce Wiggle and Go!, a two-stage framework…
One Hand to Rule Them All: Canonical Representations for Unified Dexterous Manipulation
Zhenyu Wei, Yunchao Yao, Mingyu Ding
Dexterous manipulation policies today largely assume fixed hand designs, severely restricting their generalization to new embodiments with varied kinematic and structural layouts.…
Mixture of Horizons in Action Chunking
Dong Jing, Gang Wang, Jiaqi Liu +7
Vision-language-action (VLA) models have shown remarkable capabilities in robotic manipulation, but their performance is sensitive to the used during…
REMAC: Self-Reflective and Self-Evolving Multi-Agent Collaboration for Long-Horizon Robot Manipulation
Puzhen Yuan, Angyuan Ma, Yunchao Yao +3
Vision-language models (VLMs) have demonstrated remarkable capabilities in robotic planning, particularly for long-horizon tasks that require a holistic understanding of the enviro…
When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?
Tongzhou Mu, Zhaoyang Li, Stanisław Wiktor Strzelecki +4
Learning policies from high-dimensional visual inputs, such as pixels and point clouds, is crucial in various applications. Visual reinforcement learning is a promising approach th…