Construction and mining

Applied Intuition enables scaled virtual testing for autonomous construction and mining systems. The evaluation of complex systems in virtual environments ensures safer, faster, and more efficient workflows for the development of multi-fleet systems for off-road use cases.
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Industry trends

The construction and mining industries have successfully deployed initial autonomy solutions to larger sites in highly controlled environments, resulting in a growing demand to deploy the same technology to smaller-scale sites and less structured use cases. 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 construction and mining 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 construction and mining technology. Teams can create scenarios with human agents walking around mining or construction vehicles, simulate connection failures with remote management systems, and model how sensors interact in the real world.
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 loaders, dozers, excavators, and haulers.
Simulate the effects of varied terrain and soil conditions to ensure robustness prior to field deployment.

Sensor placement analysis

Prior to on-vehicle testing, analyze sensor configurations 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 articulation

Analyze the interaction between multiple collaborating autonomous systems, such as dozers, excavators, and their implements.
Conduct design tests to analyze the operational efficiency of a site with a fleet of collaborating autonomous systems.


Reduce reliance on real-world testing

Enable 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. 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 these scenarios automatically. Uncover performance trends and capability gaps that help teams allocate engineering resources effectively.

“[Applied Intuition’s] impressive and modern technology stack brought us in, and their professionalism, passion, and attention to detail made us stay.”
Joel Skoghammer
Lead Engineer of Autonomous Transport Solution

Get started with Applied Intuition for construction and mining

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