MAPPING AND TRACKING SYSTEM

摘要

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.

主权项

1. A method for real-time tracking of features, the method comprising:
acquiring a collection of images and one or more subsequent collections of images to create a three-dimensional space, wherein the collection of images and the one or more subsequent collections of images are substantially simultaneously captured from multiple sources; identifying a candidate feature in the three-dimensional space for tracking; and tracking the candidate feature in the three-dimensional space over time.