Mapping and tracking system with features in three-dimensional space
US10750155B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jun 14, 2018 |
| Grant date | Aug 18, 2020 |
| Priority date | — |
| Expiry date | Jun 14, 2038 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N2013/0092
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
LK-SURF, Robust Kalman Filter, HAR-SLAM, and Landmark Promotion SLAM methods are disclosed. LK-SURF is an image processing technique that combines Lucas-Kanade feature tracking with Speeded-Up Robust Features to perform spatial and temporal tracking using stereo images to produce 3D features can be tracked and identified. The Robust Kalman Filter is an extension of the Kalman Filter algorithm that improves the ability to remove erroneous observations using Principal Component Analysis and the X84 outlier rejection rule. Hierarchical Active Ripple SLAM is a new SLAM architecture that breaks the traditional state space of SLAM into a chain of smaller state spaces, allowing multiple tracked objects, multiple sensors, and multiple updates to occur in linear time with linear storage with respect to the number of tracked objects, landmarks, and estimated object locations. In Landmark Promotion SLAM, only reliable mapped landmarks are promoted through various layers of SLAM to generate larger maps.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.