Model-based control with uncertain motion model

This invention describes a smart controller for robots that uses a probabilistic filter to understand the robot's current situation. It constantly learns and updates how uncertain its own understanding is, specifically by adjusting a complex mathematical model of uncertainty based on new data. This allows the robot to adapt its behavior while always respecting its physical limitations or operational rules.

Why it matters: Since 2022, advancements in probabilistic machine learning frameworks and increased computational power have made real-time learning and updating of complex uncertainty models, like time-varying Gaussian processes, more practical for adaptive robotic control.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedComplex control algorithms, robotic system integration

3 AI reinvention directions for this patent

See all three

AI gives you a few directions you could take this. Pick one, and we check whether your version is different enough to patent, then write the filing.

Reinvent this with AI

Where this one came from

Every morning we go through millions of abandoned patents and pick out 15 worth your time. This was one of today’s.

This one

+10