Nvidia patents car system that combines sensor data to map roads better
Nvidia describes a system for self-driving cars that combines data from multiple different sensors to create a more accurate map of the road. By checking if these separate data sources agree with each other, the system can detect errors and plan a safer path through turns and intersections.
In the filing’s own words
In various examples, a path perception ensemble is used to produce a more accurate and reliable understanding of a driving surface and/or a path there through. For example, an analysis of a plurality of path perception inputs provides testability and reliability for accurate and redundant lane mapping and/or path planning in real-time or near real-time. By incorporating a plurality of separate path perception computations, a means of metricizing path perception correctness, quality, and reliability is provided by analyzing whether and how much the individual path perception signals agree or disagree. By implementing this approach—where individual path perception inputs fail in almost independent ways—a system failure is less statistically likely. In addition, with diversity and redundancy in path perception, comfortable lane keeping on high curvature roads, under severe road conditions, and/or at complex intersections, as well as autonomous negotiation of turns at intersections, may be enabled.
What exactly they claim (claim 1)
1. An autonomous or semi-autonomous machine comprising: one or more central processing units (CPUs); one or more graphics processing units (GPUs); one or more hardware accelerators; and one or more external sensors having one or more fields of view or one or more sensory fields external to the autonomous or semi-autonomous machine, wherein the autonomous or semi-autonomous machine is to: determine at least a first feature representation associated with a first source and a second feature representation associated with a second source that is different from the first source; determine, based at least on the first feature representation being related to the second feature representation, a fused feature representation using the first feature representation and the second feature representation; and perform, based at least on the fused feature representation, one or more planning, navigation, or control operations.
Facts
- Company
- Nvidia (NVIDIA Corporation)
- Official title
- FEATURE DETECTION
- Publication number
- US20260279202A1
- Application number
- 19668345
- Filed
- May 5, 2026
- Published
- Sep 17, 2026
- Inventors
- 5
- Claims
- 20
Classified under
G08G 1/167 Physics & computingG05D 1/617 Physics & computingG05D 1/648 Physics & computingG05D 1/65 Physics & computingG05D 1/81 Physics & computingG06F 18/23 Physics & computingMore from Nvidia in Cars & transport
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.