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robot manipulation

6 articles · Page 1 of 1
Machine Heart
Machine Heart
Aug 10, 2026 · Artificial Intelligence

Beyond Fei‑Fei Li’s T‑Rex: Daimon’s Tactile‑Grounded World Model Gives Robots an Interaction Brain

Daimon‑TWM, the world’s first tactile‑grounded model, combines massive tactile data, perception‑to‑reasoning pipelines and fast‑feedback control to let robots predict and adapt to physical interactions, achieving dramatically higher success rates than vision‑only or prior tactile models, even under disturbances.

Daimon‑TWMbenchmarkembodied AI
0 likes · 12 min read
Beyond Fei‑Fei Li’s T‑Rex: Daimon’s Tactile‑Grounded World Model Gives Robots an Interaction Brain
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Jul 27, 2026 · Artificial Intelligence

How 30,000 Hours of Tactile Data Give Embodied AI a Human‑like Sense of Touch

The article presents a 30,000‑hour multimodal tactile‑visual dataset, unified representation models, and two downstream systems (VTLA and TWAM) that demonstrate how large‑scale touch data can dramatically improve robot manipulation success rates and establish tactile perception as a core scaling law for embodied intelligence.

embodied AImultimodal learningrobot manipulation
0 likes · 9 min read
How 30,000 Hours of Tactile Data Give Embodied AI a Human‑like Sense of Touch
Machine Heart
Machine Heart
Jul 12, 2026 · Artificial Intelligence

Predictive and Reactive Tactile Modeling: Making Robot Actions Truly Successful

The TouchWorld model combines predictive tactile forecasting with fast reactive correction, enabling robots to anticipate contact patterns before motion and instantly adjust during execution, achieving up to 65% success on six real‑world tasks and outperforming baselines by over 15 percentage points.

Foundation ModelPredictive Modelingembodied AI
0 likes · 14 min read
Predictive and Reactive Tactile Modeling: Making Robot Actions Truly Successful
Machine Heart
Machine Heart
Jun 7, 2026 · Artificial Intelligence

How RoboScience’s Bi-Adapt Framework Tackles Embodied Intelligence Generalization Bottlenecks

RoboScience’s team secured consecutive ICRA best‑paper finalist spots with Bi‑Adapt and D(R,O) Grasp, presenting a few‑shot bimanual adaptation framework and a unified grasp model that together bridge top‑tier research to scalable embodied AI by overcoming cross‑category generalization challenges.

ICRAVLOAbimanual adaptation
0 likes · 11 min read
How RoboScience’s Bi-Adapt Framework Tackles Embodied Intelligence Generalization Bottlenecks
Machine Heart
Machine Heart
May 6, 2026 · Artificial Intelligence

Beyond VLA: How Tactile Sensing Redefines Embodied AI with VTLA

In an IEEE Spectrum interview, robotics veteran Wang Yu argues that the vision‑language‑action (VLA) paradigm lacks the physical feedback needed for reliable manipulation, proposes a vision‑tactile‑language‑action (VTLA) framework, and details the open‑source Daimon‑Infinity tactile dataset and sensor technology that aim to reshape embodied AI.

VTLAdata setsembodied AI
0 likes · 13 min read
Beyond VLA: How Tactile Sensing Redefines Embodied AI with VTLA