Sold by: Duality Robotics
Deployed on AWS
Virtual worlds for solving real problems.
Falcon is a Digital Twin Simulation Platform trusted by leading robotics and AI/smart systems teams to help solve complex engineering problems. Users bring accurate digital twins of their environments and operating systems into Falcon where they can then generate high-fidelity data and predictive behavior modeling. This data enables users to develop and deploy automated systems robustly and at scale.
Overview
Falcon is the Digital Twin Simulation Platform helping transform the way users develop and deploy smart systems with domain tailored simulation designed to meet high-fidelity needs of any use case. Falcon is trusted by leading robotics and AI/smart systems teams as a complete spatial simulation solution that combines speed and accuracy with unparalleled accessibility. Accurate synthetic data and predictive behavior modeling generated in Falcon help our customers successfully bridge the Sim2Real gap.
Highlights
- Sim2real: Tune system twins and virtual sensors to match observed data and proven data permeability from simulation output as verified by demanding Fortune 100 customers. Run Open-Loop simulation for synthetic data generation or Closed-Loop for autonomous systems validation and process automation - collaboratively and in the cloud.
- Context: Quickly setup diverse scenarios using Unreal Engine based Editor and a massive catalog of simulation ready system, item and space twins.
- Intelligence: Python API and Falcon middleware integrates with proprietary and open source messaging protocols like ROS/ROS2 and the latest generation of AI models.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
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Features and programs
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
g4dn.xlarge Recommended | $0.99 |
g4dn.2xlarge | $0.99 |
g4dn.4xlarge | $0.99 |
Vendor refund policy
We do not support refunds currently, but you can cancel at anytime.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
SAR sensor v1.1 The SAR sensor has been updated to v1.1, adding orthorectification and energy-target output capabilities as specified by General Dynamics requirements.
Environment twins updated - Sedona, Downtown, Laurel The Sedona, Downtown, and Laurel environment twins have been refreshed for the 6.1 build cycle with updated assets and lighting configurations.
Unreal Engine upgraded to 5.6 FalconSim 6.1 is built on Unreal Engine 5.6, bringing the latest rendering, physics, and tooling improvements from Epic Games.
IR sensor Phase 3 - material setup integrated into FalconEditor PBIR Phase 3 material setup for environment twins is now integrated directly into FalconEditor, streamlining IR-ready environment twin creation. Note: environment twins from 5.x must be manually updated to conform to the new IR setup requirements.
Additional details
Usage instructions
Carefully review EC2 hourly prices and select the instance type that fits your budget and bandwidth requirements. We recommend g4dn.xlarge as Falcon requires a Tesla T4 GPU to operate.
Launch the instance with the desired instance type and connect to the instance by going to https://<instance ip address>:8443/#console . The instance is pre-configured with NiceDCV.
The initial login is "ubuntu" for the username and the instance ID for the password. Be sure to change the password to something only you know after logging in.
FalconSim and FalconEditor are installed and configured on your instance. You will find the readme.txt file on your desktop; this file contains basic operating instructions.
Remember to stop your instances when you don't need them to avoid EC2 hourly charges. Note that when you start your instance again, it will receive a new public IP address; you can use Elastic IP addresses to make your instances always have a permanent public IP address. As you need, create instances in multiple regions. Terminate instances when you no longer need them.
Resources
Vendor resources
Support
Vendor support
For any questions or queries regarding the usage of Falcon please refer to our tailored documentation with detailed examples to help you get started. If you still feel stuck please contact us at support+AWS@duality.ai with AWS Falcon YourSubject in the email title. Our support team aims to respond within one business day. Expect a reply to the email address you used to send the query. If you are keen on a support call or on demand training please use the support email ID.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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