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NVIDIA · Robotics Dev Blog

19天前更新

HISTORY近 30 天历史柱高表示当天去重热搜数量

3026 3027 3028 3129 3030 3031 3001 3002 3003 3004 3205

07/26—08/24 有历史数据

01
Beyond VLAs: How World Action Models Reshape Robot Manipulation
A central challenge in robotics is building policies that generalize beyond the demonstrations they’re trained on. A policy that succeeds in a training scene...Michelle Horton
02
Generate Trajectories, Reasoning Traces, and Auto-Labels with NVIDIA Alpamayo 2 Super
Autonomous vehicle (AV) development often relies on separate models for trajectory generation, high-level intent prediction, scene understanding, and data...Elizabeth Goodman
03
Developing Healthcare Robotics with GPU-Native Medical Physics Simulation
Unlike autonomous driving or industrial robotics, healthcare robotics can’t rely on internet-scale data collection or unlimited real-world experimentation....Michelle Horton
04
Develop Lightweight USD Runtimes Faster with AI Agents
OpenUSD is an open, extensible framework that provides a common scene description language for physical AI. It enables teams to bring CAD data, simulation...Michelle Horton
05
How to Evaluate General-Purpose Robot Policies for Real-World Deployment
Robotics foundation models have made remarkable progress. Today's best systems can follow natural language instructions to pick, place, sort, and manipulate a...Brad Nemire
06
Develop Humanoid Robot Policies End-to-End with NVIDIA Isaac GR00T
As more teams move from humanoid robot bring-up to task-specific skill development, the need for repeatable development workflows is growing. Building humanoids...Elizabeth Goodman
07
Inside NVIDIA Halos for Robotics: A Full-Stack Functional Safety System for Physical AI
Physical AI—robots working autonomously alongside people in factories, warehouses, hospitals, and homes—is arriving faster than most expected. Traditional...Suhas Hariharapura Sheshadri
08
Pretrained to Imagine, Fine-Tuned to Act: The Rise of World-Action Models
Quick glossary for readers new to VLA/WAM terminology VLA Vision-Language-Action model: a robot policy that starts from a pretrained VLM backbone and adapts it...Moritz Reuss
09
Deploy Agentic-Ready AI at the Edge with Memory Efficiency in NVIDIA JetPack 7.2
As AI agents move from the digital world to the physical environment, they can readily use NVIDIA Jetson to accelerate real-world deployment with optimized...Peilun Tsai
10
How to Post-Train Autonomous Vehicle Models in Closed-Loop with NVIDIA Alpamayo
Developing autonomous vehicle (AV) policies requires bridging an important gap between training and deployment. Vision-language-action (VLA) models that can...Boris Ivanovic
11
Develop Physical AI Reasoning, World, and Action Models with NVIDIA Cosmos 3
Physical AI systems must understand the real world before they can act within it. Robots, autonomous vehicles, and smart spaces need to understand what's...Asawaree Bhide
12
Maximizing Memory Efficiency with Agent Skills to Run Bigger Models on NVIDIA Jetson
The boom in open source generative AI models is pushing beyond data centers into machines operating in the physical world. Developers are eager to deploy these...Anshuman Bhat
13
Integrate Physical AI Capabilities into Existing Apps with NVIDIA Omniverse Libraries
Physical AI—AI systems that perceive, reason, and act in physically grounded simulated environments—is changing how teams design and validate robots and...Ashley Goldstein
14
Build and Stream Browser-Based XR Experiences with NVIDIA CloudXR.js
Delivering high-fidelity VR and AR experiences to enterprise users has typically required native application development, custom device management, and complex...Yanzi Zhu
15
How Centralized Radar Processing on NVIDIA DRIVE Enables Safer, Smarter Level 4 Autonomy
In the current state of automotive radar, machine learning engineers can't work with camera-equivalent raw RGB images. Instead, they work with the output of...Lachlan Dowling
16
NVIDIA IGX Thor Powers Industrial, Medical, and Robotics Edge AI Applications
Industrial and medical systems are rapidly increasing the use of high-performance AI to improve worker productivity, human-machine interaction, and downtime...Suhas Hariharapura Sheshadri
17
Using Simulation to Build Robotic Systems for Hospital Automation
Healthcare faces a structural demand–capacity crisis: a projected global shortfall of ~10 million clinicians by 2030, billions of diagnostic exams annually...Mingxin Zheng
18
Newton Adds Contact-Rich Manipulation and Locomotion Capabilities for Industrial Robotics
Physics forms the foundation of robotic simulation, enabling realistic modeling of motion and interaction. For tasks like locomotion and manipulation,...Philipp Reist
19
Scale Synthetic Data and Physical AI Reasoning with NVIDIA Cosmos World Foundation Models
The next generation of AI-driven robots like humanoids and autonomous vehicles depends on high-fidelity, physics-aware training data. Without diverse and...Pranjali Joshi
20
Build Accelerated, Differentiable Computational Physics Code for AI with NVIDIA Warp
Computer-aided engineering (CAE) is shifting from human-driven workflows toward AI-driven ones, including physics foundation models that generalize across...Sheel Nidhan
21
Build Next-Gen Physical AI with Edge‑First LLMs for Autonomous Vehicles and Robotics
Physical AI is rapidly evolving, from next-generation software-defined autonomous vehicles (AVs) to humanoid robots. The challenge is no longer how to run a...Lin Chai
22
R²D²: Scaling Multimodal Robot Learning with NVIDIA Isaac Lab
Building robust, intelligent robots requires testing them in complex environments. However, gathering data in the physical world is expensive, slow, and often...Oyindamola Omotuyi
23
Building Generalist Humanoid Capabilities with NVIDIA Isaac GR00T N1.6 Using a Sim-to-Real Workflow
To make humanoid robots useful, they need cognition and loco-manipulation that span perception, planning, and whole-body control in dynamic environments. ...Edith Llontop
24
Accelerating LLM and VLM Inference for Automotive and Robotics with NVIDIA TensorRT Edge-LLM
Large language models (LLMs) and multimodal reasoning systems are rapidly expanding beyond the data center. Automotive and robotics developers increasingly want...Lin Chai
25
Build and Orchestrate End-to-End SDG Workflows with NVIDIA Isaac Sim and NVIDIA OSMO
As robots take on increasingly dynamic mobility tasks, developers need physics-accurate simulations that translate across environments and workloads. Training...Asawaree Bhide
26
Simplify Generalist Robot Policy Evaluation in Simulation with NVIDIA Isaac Lab-Arena
Generalist robot policies must operate across diverse tasks, embodiments, and environments, requiring scalable, repeatable simulation-based evaluation. Setting...Sangeeta Subramanian
27
Accelerate AI Inference for Edge and Robotics with NVIDIA Jetson T4000 and NVIDIA JetPack 7.1
NVIDIA is introducing the NVIDIA Jetson T4000, bringing high-performance AI and real-time reasoning to a wider range of robotics and edge AI applications....Shashank Maheshwari
28
Building Autonomous Vehicles That Reason with NVIDIA Alpamayo
Autonomous vehicle (AV) research is undergoing a rapid shift. The field is being reshaped by the emergence of reasoning-based vision–language–action (VLA)...Marco Pavone
29
AI Factories, Physical AI, and Advances in Models, Agents, and Infrastructure That Shaped 2025
2025 was another milestone year for developers and researchers working with NVIDIA technologies. Progress in data center power and compute design, AI...Michelle Horton
30
Simulate Robotic Environments Faster with NVIDIA Isaac Sim and World Labs Marble
Building realistic 3D environments for robotics simulation has traditionally been a labor-intensive process, often requiring weeks of manual modeling and setup....Wonsik Han