Applied Intuition enables scaled virtual testing for autonomous agriculture systems. The evaluation of complex systems in virtual environments ensures safer, faster, and more efficient development workflows for field operations, multi-robot coordinations, and field-to-field transits.
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Industry trends

The agriculture industry has successfully deployed precision agriculture solutions for commercial commodity crops, resulting in a growing demand to deploy the same technology to smaller-scale farms and specialty crops. To meet this demand, autonomy solutions must be scalable, cost-effective for providers, and safe for customers. As real-world testing can be costly, dangerous, and difficult to scale, virtual testing is necessary to safely deploy autonomous agriculture systems at scale.

Applied Intuition’s approach

Applied Intuition’s integrated toolchain of simulation and data products enables entire programs to collaborate and speed up the safe development of autonomous agriculture technology. Teams can safely develop automated field operations, generate virtual environments, simulate a fleet of autonomous robot systems, and test transit to the field and back to the machinery shed.
Performant physics-based simulation
Enable accurate simulation results with correlated sensor models, physically based rendering materials across environments and assets, and highly accurate vehicle dynamics models.
Scaled test case creation and execution
Rapidly create and run tests at scale to provide test coverage for complex systems and operational design domains (ODDs) with continuous validation workflows.
Performance analysis and reporting
Enable more efficient operations with a platform that surfaces insights across synthetic and field data to efficiently allocate engineering resources toward the highest-priority issues.

Vehicle dynamics development

Run virtual tests with accurate and performant vehicle dynamics models for heavy equipment such as tractors, harvesters, and grain carts.
Simulate the effects of varied terrain and soil conditions to ensure robustness prior to field deployment.

Sensor placement analysis

Analyze sensor configurations prior to on-vehicle testing with physically accurate sensor models and environments.
Evaluate engineering trade-offs for different use cases, including perception systems, operator awareness, or calibration and stitching systems.

Virtual testing

Evaluate autonomy systems prior to site deployment.
Use virtual environments to build test cases, obtain key metrics, and verify system performance in simulation.
Scale testing across multiple vehicles, deployments, and ODDs.

Multi-ego interaction and trailering

Analyze the interaction between multiple collaborating autonomous systems, such as grain carts and harvesters.
Understand performance variations with a variety of different trailers and implements.


Reduce reliance on real-world testing

Enable year-round testing across all conditions at any point in the development cycle with simulation, reducing the number of issues identified closer to deployment.

Achieve coverage for an ODD

Utilize virtual testing for edge cases that are difficult to test or rarely observed in the field, and combine virtual testing with real-world tests to achieve a unified view of test coverage.

Verify system performance

Rapidly create thousands of scenarios and methods to use built-in ground truth information and evaluate scenarios automatically. Uncover performance trends and capability gaps to help teams allocate engineering resources effectively.

Get started with Applied Intuition for agriculture

Learn how to develop, test, and validate autonomous agriculture systems faster, more safely, and more cost-efficiently.
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