# US 12,002,371 B2 · Neuromorphic cameras for aircraft > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,002,371 B2 - Document ID: US12002371B2 - Status: Granted - Kind: B2 - Application number: 17/321,232 - Filed: 2021-05-14 - Published: 2022-11-17 - Granted: 2024-06-04 - Earliest claimed: 2021-05-14 - Assignees: Rockwell Collins, Inc. - Applicants: Rockwell Collins, Inc. - Inventors: Julian C. Ryde; Weston J. Lahr; Richard M. Rademaker - Web page: https://patentgrep.com/patent/US12002371B2 ## CPC - G06V 20/588: {Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road} - G08G 5/54: for approach or landing - G06V 10/14: Optical characteristics of the device performing the acquisition or on the illumination arrangements - G06V 10/751: {Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching} - G06V 10/766: using regression, e.g. by projecting features on hyperplanes - G06V 20/13: Satellite images - G06V 20/17: taken from planes or by drones - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) ## Abstract An onboard aircraft landing system includes one or more event-based cameras disposed at known locations to capture the runway and visible surrounding features such as lights and runway markings. The event-based cameras produce a continuous stream of event data that may be quickly processed to identify both light and dark features contemporaneously, and calculate an aircraft pose relative to the runway based on the identified features and the known locations of the event-based cameras. Composite features are identified via the relative location of individual features corresponding to pixel events. ## Claims ### Claim 1 A computer apparatus comprising: one or more event-based cameras; and at least one processor in data communication with the one or more event-based cameras and a memory storing processor executable code for configuring the at least one processor to: receive a continuous stream of pixel change events from each of the one or more event-based cameras; identify one or more light sources via the continuous stream of pixel change events; identify one or more low-light features via the continuous stream of pixel change events; and determine a pose estimate for a platform including the one or more event-based cameras based on the identified one or more light sources and the identified one or more low-light features, wherein the one or more light sources and identified one or more low-light features are related by known, standard relative locations. ### Claim 2 (depends on 1) The computer apparatus of claim 1, wherein the at least one processor is further configured to identify at least one composite feature based on a relative disposition of two or more of the identified light sources and identified low-light features. ### Claim 3 (depends on 1) The computer apparatus of claim 1, wherein the at least one processor is further configured to identify a flashing LED light source. ### Claim 4 (depends on 1) The computer apparatus of claim 1, wherein identifying the one or more light sources comprises executing a random sample consensus algorithm. ### Claim 5 (depends on 4) The computer apparatus of claim 4, wherein the at least one processor is further configured to organize pixel change events in an x/y-time space. ### Claim 6 (depends on 1) The computer apparatus of claim 1, wherein the at least one processor is further configured to identify one or more edge features via the continuous stream of pixel change events. ### Claim 7 (depends on 1) The computer apparatus of claim 1, wherein the at least one processor is further configured to correlate locations of the identified light sources and the identified low-light features in time based on time stamps of the pixel change events. ### Claim 8 An aircraft landing system comprising: one or more event-based cameras disposed at known locations on an aircraft to capture images of a runway during a landing procedure; and at least one processor in data communication with the one or more event-based cameras and a memory storing processor executable code for configuring the at least one processor to: receive a continuous stream of pixel change events from each of the one or more event-based cameras; identify one or more light sources via the continuous stream of pixel change events; identify one or more low-light features via the continuous stream of pixel change events; and determine a pose estimate for the aircraft based on the identified one or more light sources and the identified one or more low-light features, wherein the one or more light sources and identified one or more low-light features are related by known, standard relative locations. ### Claim 9 (depends on 8) The aircraft landing system of claim 8, wherein the at least one processor is further configured to identify at least one composite feature based on a relative disposition of two or more of the identified light sources and identified low-light features. ### Claim 10 (depends on 8) The aircraft landing system of claim 8, wherein the at least one processor is further configured to identify a flashing LED light source. ### Claim 11 (depends on 8) The aircraft landing system of claim 8, wherein identifying the one or more light sources comprises executing a random sample consensus algorithm. ### Claim 12 (depends on 11) The aircraft landing system of claim 11, wherein the at least one processor is further configured to organize pixel change events in an x/y-time space. ### Claim 13 (depends on 8) The aircraft landing system of claim 8, wherein the at least one processor is further configured to identify one or more edge features via the continuous stream of pixel change events. ### Claim 14 (depends on 8) The aircraft landing system of claim 8, wherein the at least one processor is further configured to correlate locations of the identified light sources and the identified low-light features in time based on time stamps of the pixel change events. ### Claim 15 A method for determining an aircraft pose estimate comprising: receiving a continuous stream of pixel change events from one or more event-based cameras; identifying one or more light sources via the continuous stream of pixel change events; identifying one or more low-light features via the continuous stream of pixel change events; and determining a pose estimate for the aircraft based on the identified one or more light sources and the identified one or more low-light features, wherein the one or more light sources and identified one or more low-light features are related by known, standard relative locations. ### Claim 16 (depends on 15) The method of claim 15, further comprising identifying at least one composite feature based on a relative disposition of two or more of the identified light sources and identified low-light features. ### Claim 17 (depends on 15) The method of claim 15, further comprising identifying a flashing LED light source. ### Claim 18 (depends on 15) The method of claim 15, wherein identifying the one or more light sources comprises executing a random sample consensus algorithm. ### Claim 19 (depends on 18) The method of claim 18, further comprising organizing pixel change events in an x/y-time space. ### Claim 20 (depends on 15) The method of claim 15, further comprising correlate locations of the identified light sources and the identified low-light features in time based on time stamps of the pixel change events.