Invention Application
- Patent Title: AUTONOMOUS VEHICLE: OBJECT-LEVEL FUSION
-
Application No.: US15280291Application Date: 2016-09-29
-
Publication No.: US20180089538A1Publication Date: 2018-03-29
- Inventor: Matthew Graham , Troy Jones , Kyra Horne , Scott Lennox , Jon D. Demerly , Stephen Sheldon Strong , Afrah Faiz Naik
- Applicant: The Charles Stark Draper Laboratory, Inc. , AutoLIV ASP, Inc.
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/00 ; G05D1/02

Abstract:
Previous self-driving car systems can detect objects separately with either vision systems, RADAR systems or LIDAR systems. In an embodiment of the present invention, an object fusion module normalizes sensor output from vision, RADAR, and LIDAR systems into a common format. Then, the system fuses the object-level sensor data across all systems by associating all objects detected and predicting tracks for all objects. The present system improves over previous systems by using the data from all sensors combined to develop a single set of knowledge about the objects around the self-driving car, instead of each sensor operating separately.
Public/Granted literature
- US10599150B2 Autonomous vehicle: object-level fusion Public/Granted day:2020-03-24
Information query