Explore how vision-language-action models like Helix, GR00T N1, and RT-1 are enabling robots to understand instructions and act autonomously.
To be useful in more dynamic and less structured environments, robots need artificial intelligence trained on a variety of sensory inputs. Microsoft Corp. today announced Rho-alpha, or ρα, the first ...
Abstract: In this paper, for manipulating flexible objects, e.g., connecting a grounding wire with the power line, in live-maintaining of power substations, we propose an action-level vision-language ...
Instructions for cuda 12.8 (Nvidia 50-- series cards): To get started with loading and running OpenVLA models for inference, we provide a lightweight interface that leverages HuggingFace transformers ...
Safely achieving end-to-end autonomous driving is the cornerstone of Level 4 autonomy and the primary reason it hasn’t been widely adopted. The main difference between Level 3 and Level 4 is the ...
This project develops a unified framework for physically grounded world modelling that combines video-based temporal prediction with Gaussian Splatting for photorealistic 3D representation. A Physics ...
VITRA is a novel approach for pretraining Vision-Language-Action (VLA) models for robotic manipulation using large-scale, unscripted, real-world videos of human hand activities. Treating human hand as ...
NVIDIA is attempting to solve the “black box” problem of self-driving cars by open-sourcing the cognitive architecture behind them. At the NeurIPS conference today, the company released Alpamayo-R1, a ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results