Crypto Flexs
  • DIRECTORY
  • CRYPTO
    • ETHEREUM
    • BITCOIN
    • ALTCOIN
  • BLOCKCHAIN
  • EXCHANGE
  • TRADING
  • SUBMIT
Crypto Flexs
  • DIRECTORY
  • CRYPTO
    • ETHEREUM
    • BITCOIN
    • ALTCOIN
  • BLOCKCHAIN
  • EXCHANGE
  • TRADING
  • SUBMIT
Crypto Flexs
Home»ADOPTION NEWS»NVIDIA Unveils AutoMate to Advance Robotic Assembly Technology
ADOPTION NEWS

NVIDIA Unveils AutoMate to Advance Robotic Assembly Technology

By Crypto FlexsJuly 11, 20243 Mins Read
Facebook Twitter Pinterest LinkedIn Tumblr Email
NVIDIA Unveils AutoMate to Advance Robotic Assembly Technology
Share
Facebook Twitter LinkedIn Pinterest Email





In a major step forward in enhancing robotics capabilities, NVIDIA has unveiled a new framework called AutoMate, which aims to train robots for assembly tasks in a variety of geometries. This innovative framework, detailed in a recent NVIDIA Technology Blog post, demonstrates its potential to bridge the gap between simulation and real-world applications.

What is AutoMate?

AutoMate is the first simulation-based framework designed to train both expert and general robot assembly skills. Developed in collaboration with the University of Southern California and the NVIDIA Seattle Robotics Lab, AutoMate demonstrates zero-shot simulation-to-real transfer of the technology, meaning that skills learned in simulation can be directly applied to real environments without any additional tuning.

The main advantages of AutoMate are:

  • A dataset consisting of 100 assemblies and a ready-to-use simulation environment.
  • An algorithm that effectively trains robots to handle various assembly tasks.
  • It is a synthesis of learning approaches that distills knowledge from multiple specialized skills into a single general skill, further enhanced by reinforcement learning (RL).
  • A real system where simulation-trained skills can be deployed in a workflow initialized by perception.

Data sets and simulation environments

AutoMate’s dataset contains 100 assemblies that are simulation-compatible and 3D-printable. These assemblies are based on Autodesk’s large dataset, allowing practical applications in real-world environments. The simulation environment is designed to parallelize tasks, improving the efficiency of the training process.

Learning expert on various geometries

While previous NVIDIA projects like IndustReal have made progress using RL, AutoMate combines RL and imitation learning to train robots more effectively. This approach addresses three main challenges: generating demos for assembly, integrating imitation learning into RL, and selecting the right demos during training.

Creating a demo through assembly and disassembly

Inspired by the assemble-disassemble concept, this process involves collecting disassembled demonstrations and reversing the process for assembly. This method simplifies the collection of demonstrations, which can be expensive and complex if done manually.

RL with imitation goals

Incorporating an imitation term into the RL reward function improves the learning process by encouraging the robot to imitate the demonstration. This approach is consistent with previous work on character animation and provides a robust framework for training.

Select a demo using dynamic time warping

Dynamic Time Warping (DTW) is used to measure the similarity between the robot path and the demonstration path, allowing the robot to follow the most effective demonstration at each step. This method improves the robot’s ability to learn from the best available examples.

Learning general assembly techniques

To develop a generalist technique that can handle multiple assembly tasks, AutoMate uses a three-step approach: behavior replication, dataset aggregation (DAgger), and RL fine-tuning. This method allows the generalist technique to benefit from the knowledge accumulated by the expert technique to improve overall performance.

Real-world setup and perception initialization workflow

The real setup includes a Franka Panda robot arm, an Intel RealSense D435 camera mounted on the wrist, and a Schunk EGK40 gripper. The workflow includes RGB-D image capture, 6D pose estimation of the part, and deployment of the assembly skills trained in simulation. This setup ensures that the trained skills can be effectively applied to real-world conditions.

summary

AutoMate represents a significant advance in robotic assembly, leveraging simulation and learning methods to solve a wide range of assembly problems. Future steps will focus on multi-part assembly and further refine the technology to meet industry standards.

For more information, visit the AutoMate project page and explore related NVIDIA environments and tools.

Image source: Shutterstock



Share. Facebook Twitter Pinterest LinkedIn Tumblr Email

Related Posts

Crypto Exchange Rollish is expanded to 20 by NY approved.

October 2, 2025

SOL Leverage Longs Jump Ship, is it $ 200 next?

September 24, 2025

Bitcoin Treasury Firm Strive adds an industry veterans and starts a new $ 950 million capital initiative.

September 16, 2025
Add A Comment

Comments are closed.

Recent Posts

Decoding City Protocol’s IP Capital Market

October 14, 2025

Tria Raises $12M To Be The Leading Self-custodial Neobank And Payments Infrastructure For Humans And AI.

October 14, 2025

How to Use Google Gemini to Analyze Crypto Coins Before Investing

October 14, 2025

Class action lawsuit claims Microsoft choked AI supply to drive up ChatGPT costs

October 14, 2025

CME Group Launches CFTC Regulated Solana and XRP Options

October 13, 2025

Eightco Holdings Inc. ($ORBS) Makes Strategic Investment Into Mythical Games To Accelerate Human Verification And Digital Identity In Gaming

October 13, 2025

Jiuzi Holdings, Inc. (JZXN) Secures 100 Bitcoin Via Private Placement, Signaling New Phase In Crypto Treasury Deployment

October 13, 2025

Collaboration Across Bybit, DigiFT And UBS UMINT Expands Collateral Solution For Institutions

October 13, 2025

BitMine Immersion (BMNR) Announces ETH Holdings Exceeding 3.03 Million Tokens And Total Crypto And Cash Holdings Of $12.9 Billion

October 13, 2025

Phemex Announces Halloween Futures Trading Festival With 200,000 USDT Prize Pool

October 13, 2025

ViaBTC Unveils Enhanced Collateralized Loan Service For Global Miners

October 13, 2025

Crypto Flexs is a Professional Cryptocurrency News Platform. Here we will provide you only interesting content, which you will like very much. We’re dedicated to providing you the best of Cryptocurrency. We hope you enjoy our Cryptocurrency News as much as we enjoy offering them to you.

Contact Us : Partner(@)Cryptoflexs.com

Top Insights

Decoding City Protocol’s IP Capital Market

October 14, 2025

Tria Raises $12M To Be The Leading Self-custodial Neobank And Payments Infrastructure For Humans And AI.

October 14, 2025

How to Use Google Gemini to Analyze Crypto Coins Before Investing

October 14, 2025
Most Popular

Bitcoin price holds support. Is a rebound coming?

August 30, 2024

Chainlink (LINK) Turns Bullish: Is the Rally Still Here or Just a Surge?

July 9, 2024

EA is looking to the metaverse to increase participation in sports games!

February 1, 2024
  • Home
  • About Us
  • Contact Us
  • Disclaimer
  • Privacy Policy
  • Terms and Conditions
© 2025 Crypto Flexs

Type above and press Enter to search. Press Esc to cancel.