Sensor fusion

Sensor fusion for autonomous machinery

Intelligence in vehicles and other machinery is a result of a myriad of critical sub-solutions. These often depend on AI models interpreting the messy real-world with the ability to predict what will happen next. This is done through gaining situational awareness through sensor fusion, be it based on mathematical modeling or deep learning.

Model motion under uncertainty and increase accuracy with sensor fusion

Autonomous vehicles

The automotive environment requires split-second decisions to avoid and mitigate accidents. A self-driving car must sense, plan and act at least in half a second.

Autonomous vessels

Marine vehicles move slowly but steadily and require precise decisions performed by the system. A miscalculation could mean that a large container ship is fated to wreck in a few minutes, regardless of efforts.

Autonomous machinery

Some major-scale mining has operated largely autonomously for a decade, and port cranes, forest machines, tugs, and other machinery are hastily preparing for the same.

Towards autonomous operations

Situational awareness holds hundreds of smaller challenges within it. However, with AI technologies, we’re accelerating the speed at which we solve them for a wide range of industries from forestry, mining, and marine to logistics and manufacturing. We’ve built intelligent mobile machines for widely varying environments and use cases.

Getting things done autonomously requires combining many fields of expertise, investigating thoroughly what is possible and how to build it, and handling the complexity of all the interlinked subproblems. Silo AI’s 240+ experts with 120+ PhDs can help you.