#Dexterous Manipulation (91)

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EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data

EgoScale is a human-to-dexterous-manipulation transfer framework. A VLA policy is pretrained on 20,854 hours of action-labeled egocentric human video, revealing a log-linear relationship between data scale and validation loss. Lightweight aligned human-robot mid-training then grounds the learned motor prior in robot control, improving average success by 54% over a no-pretraining baseline on a 22-DoF dexterous hand and transferring to lower-DoF hands.

Ruijie Zheng, Dantong Niu, Yuqi Xie · 150 views · Feb 18, 2026

Dexterous ManipulationVLA

Feb 18, 2026

4:02

FACT: Learning Dexterous Manipulation from Video and Force

@RavenHuang4 · 115 views · 2026-10-28

FACTDexterous Manipulation

Self-Adaptive VLA for Robust Robot Deployment

This post-training method turns a policy's own shifted rollouts into latent context, uses a lightweight encoder and adaptive layer normalization to adapt a vision-language-action policy, and recovers over 80% of base performance across four precision-critical manipulation tasks.

Hongxin Zhang, Chunru Lin, Tsun-Hsuan Wang · 157 views · Sep 24, 2026

VLATest-Time Adaptation

Sep 24, 2026

0:58

GPT-6 Astra Reconstructs Human Sphere Play with a Sharpa Hand

@memmelma · 173 views · 2026-10-23

Dexterous ManipulationMotion retargeting

DONIC: Generalist Dexterous Bimanual Tracking Control from Human Demonstrations

Despite recent progress in dexterous reference tracking, existing models focus primarily on single-hand manipulation and a limited range of interactions, leaving the bimanual dexterous behaviors common in real life unaddressed. The scarcity of contact-rich bimanual manipulation data and the increased complexity of coordinating contacts make developing a generalist bimanual tracker particularly challenging. Therefore, we present 1) DONIC, the first generalist bimanual tracker jointly trained across operation categories and human-motion sources, together with 2) BiHOI, a multi-view dataset of 1,575 sequences spanning 229 objects and emphasizing sustained bimanual interaction, where reconstructed interactions are retargeted into robot references. DONIC combines proximal policy optimization with behavioral cloning in a feedback loop that recycles verified successful executions into training demonstrations. An object-centered per-hand reward maintains object-motion feedback while supervising each hand according to its reference contact role. Clip-Centered Advantages remove reference-dependent advantage offsets while preserving within-trajectory differences. Together, these designs enable one single policy to learn coordinated manipulation across heterogeneous references. Without finetuning, a single checkpoint achieves 86.79% success on unseen trajectories of training objects and 57.32% on held-out objects, surpassing the state-of-the-art bimanual tracking baselines by 77.36 and 45.73 percentage points.

Mingze Sun, Ziang Cao, Yuan Fei · 219 views · Oct 21, 2026

Dexterous ManipulationBimanual Manipulation

Oct 21, 2026

1:24

DONIC: One Policy, Two Dexterous Hands for Bimanual Tracking

@HuggingPapers · 151 views · 2026-10-22

Dexterous ManipulationBimanual Control

T-WLA: Bridging Slow Vision and Fast Touch

T-WLA shares a history-aware visual memory between a slow vision-language-action policy and a fast tactile residual editor. The visual branch produces an action chunk and memory at 39.7 Hz; the lightweight tactile editor reuses them to correct only unexecuted actions at 119.1 Hz. It improves tactile-conditioned hand-motion prediction and contact-rich manipulation, reaching 50.0% average success on four real-robot tasks with 30 demonstrations each.

Kaichen Zhou, Yuzhen Chen, Hannah Yao · 271 views · Oct 20, 2026

Tactile SensingVisuotactile Manipulation

Oct 20, 2026

1:41

Aero Hand Open: A $314 Open-Source Tendon-Driven Dexterous Hand

@techniahqrobot · 191 views · 2026-10-18

Dexterous ManipulationRobot Hand

0:52

FOMO-Dex brings force modulated dexterity to compliant teleoperation

@Ying_yyyyyyyy · 184 views · 2026-10-15

FOMO-DexDexterous Manipulation

7:59

GEN-1.5 Runs a Continuous Cosmetics-Kit Assembly

@GeneralistAI · 173 views · 2026-10-15

Robot foundation modelsDexterous Manipulation

Systematically Exploring the Capabilities of GPT-6 Astra as Embodied Policies

Evaluates GPT-6 Astra as an embodied policy across six domains: hybrid control reaches 48% on RoboDojo and 92% on RxR navigation, while direct in-hand control and dense locomotion references stay unreliable; token use and inference latency constrain practical control.

Galbot Team, Chen, Xuchuan, Cheng, Xiaoqian · 525 views · Sep 29, 2026

Embodied AIRobot Manipulation

Sep 29, 2026