Obstacle to path assignment and performance of control operations based on assignment for autonomous systems and applications
US12346119B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 30, 2021 |
| Grant date | Jul 1, 2025 |
| Priority date | — |
| Expiry date | Feb 15, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05D2111/30
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
In various examples, one or more output channels of a deep neural network (DNN) may be used to determine assignments of obstacles to paths. To increase the accuracy of the DNN, the input to the DNN may include an input image, one or more representations of path locations, and/or one or more representations of obstacle locations. The system may thus repurpose previously computed information—e.g., obstacle locations, path locations, etc.—from other operations of the system, and use them to generate more detailed inputs for the DNN to increase accuracy of the obstacle to path assignments. Once the output channels are computed using the DNN, computed bounding shapes for the objects may be compared to the outputs to determine the path assignments for each object. Additionally, a machine may perform control operations based at least on the path assignments.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.