# US 11,908,075 B2 · Generating and filtering navigational maps > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,908,075 B2 - Document ID: US11908075B2 - Status: Granted - Kind: B2 - Application number: 17/523,850 - Filed: 2021-11-10 - Published: 2023-05-11 - Granted: 2024-02-20 - Earliest claimed: 2021-11-10 - Assignees: Valeo Schalter und Sensoren GmbH - Applicants: Valeo Schalter und Sensoren GmbH - Inventors: Sree Harsha Chowdary Gorantla - Web page: https://patentgrep.com/patent/US11908075B2 ## CPC - G01C 21/3804: {Creation or updating of map data} - G06T 17/05: Geographic models - G01S 7/4808: {Evaluating distance, position or velocity data} - G01S 17/89: for mapping or imaging - G06T 7/70: Determining position or orientation of objects or cameras (camera calibration G06T7/80) - G06V 20/56: exterior to a vehicle by using sensors mounted on the vehicle - G01C 21/36: Input/output arrangements for on-board computers - G01C 21/3602: {Input other than that of destination using image analysis, e.g. detection of road signs, lanes, buildings, real preceding vehicles using a camera} - G06T 2207/10028: Range image; Depth image; 3D point clouds - G06T 2207/30252: Vehicle exterior; Vicinity of vehicle - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract Described are techniques for generating, updating, and using sensor-based navigational maps. An input map is generated based on sensor data captured by a first sensor of a first vehicle. The input map is filtered based on one or more criteria to generate a filtered map corresponding to a three-dimensional representation of a route traveled by the first vehicle. The filtering can be based on detecting features using sensor data captured by a second sensor of the first vehicle. The one or more criteria can include object classes, distance criteria, and/or other criteria relating to attributes of features in the sensor data captured by the first sensor and/or the sensor data captured by the second sensor. The filtered map can be stored for transmission to a second vehicle, for use in determining a location of the second vehicle while the second vehicle is traveling along the same route. ## Claims ### Claim 1 A method for generating a map, the method comprising: generating, by a computer system and based on sensor data captured by a first sensor of a first vehicle, an input map corresponding to a three-dimensional representation of a route traveled by the first vehicle; detecting, by the computer system, objects represented in the sensor data, wherein the detecting comprises assigning a corresponding class label to features associated with the same object, each class label being selected from a set of predefined object classes; generating, by the computer system, a bounding box around each detected object; filtering, by the computer system and based on one or more criteria, the input map to generate a filtered map, wherein: the filtering comprises automatically removing features that satisfy the one or more criteria, the one or more criteria identify objects that are irrelevant to determining a location of a second vehicle with reference to the filtered map, and the one or more criteria comprise at least one object class such that at least some features are removed based on having been assigned a class label corresponding to the at least one object class and further based on belonging to the same bounding box; and transmitting, by the computer system, the filtered map to the second vehicle, wherein the filtered map is processed by a navigation system of the second vehicle to determine a location of the second vehicle while the second vehicle is traveling along the same route. ### Claim 2 (depends on 1) The method of claim 1, wherein the at least one object class comprises at least one of vehicles, pedestrians, animals, or plants. ### Claim 3 (depends on 1) The method of claim 1, wherein the one or more criteria comprise at least one attribute of an object to be removed, the at least one attribute including at least one of age, length, width, height, speed, or shape. ### Claim 4 (depends on 1) The method of claim 1, wherein the one or more criteria comprise a distance from the first vehicle, the distance being a threshold distance beyond which features are to be removed. ### Claim 5 (depends on 1) The method of claim 1, wherein the filtered map indicates edges of a multi-lane road along the route, and wherein the filtered map excludes lanes within the multi-lane road. ### Claim 6 (depends on 1) The method of claim 1, wherein the first sensor is a LIDAR sensor, wherein the input map comprises a point cloud captured by the LIDAR sensor, and wherein the filtering comprises removing points that satisfy the one or more criteria. ### Claim 7 (depends on 6) The method of claim 6, wherein detecting objects represented in the sensor data further comprises: identifying features belonging to the same object using the point cloud together with additional sensor data captured by a second sensor of the first vehicle, wherein the additional sensor data is captured contemporaneously with the point cloud, and wherein the second sensor is a camera, a radar sensor, or another LIDAR sensor. ### Claim 8 (depends on 7) The method of claim 7, wherein the second sensor is a camera, and wherein generating a bounding box around each detected object comprises: determining two-dimensional boundaries of objects in an image captured by the camera; and mapping the two-dimensional boundaries to corresponding regions of the point cloud to form three-dimensional bounding boxes around points in the point cloud. ### Claim 9 (depends on 1) The method of claim 1, wherein the filtering comprises: performing a first filtering operation in which features corresponding to ground reflections and moving objects are removed from the input map, the moving objects being removed through point motion classification; and performing a second filtering operation after the first filtering operation, the second filtering operation removing features that have been assigned a class label corresponding to the at least one object class. ### Claim 10 (depends on 1) The method of claim 1, wherein the filtered map is transmitted to the second vehicle through a wireless connection while the second vehicle is traveling along the same route, and wherein to determine the location of the second vehicle, features included in the filtered map are matched to corresponding features in sensor data captured by a sensor of the second vehicle. ### Claim 11 A system comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to: generate, based on sensor data captured by a first sensor of a first vehicle, an input map corresponding to a three-dimensional representation of a route traveled by the first vehicle; detect objects represented in the sensor data, wherein the one or more processors are configured to detect objects through assigning a corresponding class label to features associated with the same object, each class label being selected from a set of predefined object classes; generate a bounding box around each detected object; filter, based on one or more criteria, the input map to generate a filtered map, wherein: to filter the input map the one or more processors are configured to automatically remove features that satisfy the one or more criteria, the one or more criteria identify objects that are irrelevant to determining a location of a second vehicle with reference to the filtered map, and the one or more criteria comprise at least one object class such that at least some features are removed based on having been assigned a class label corresponding to the at least one object class and further based on belonging to the same bounding box; and transmit the filtered map to the second vehicle, wherein the filtered map is usable by a navigation system of the second vehicle to determine a location of the second vehicle while the second vehicle is traveling along the same route. ### Claim 12 (depends on 11) The system of claim 11, wherein the at least one object class comprises at least one of vehicles, pedestrians, animals, or plants. ### Claim 13 (depends on 11) The system of claim 11, wherein the one or more criteria comprise at least one attribute of an object to be removed, the at least one attribute including at least one of age, length, width, height, speed, or shape. ### Claim 14 (depends on 11) The system of claim 11, wherein the one or more criteria comprise a distance from the first vehicle, the distance being a threshold distance beyond which features are to be removed. ### Claim 15 (depends on 11) The system of claim 11, wherein the filtered map indicates edges of a multi-lane road along the route, and wherein the filtered map excludes lanes within the multi-lane road. ### Claim 16 (depends on 11) The system of claim 11, wherein: the first sensor is a LIDAR sensor; the input map comprises a point cloud captured by the LIDAR sensor; the one or more processors are configured to identify features belonging to the same object using the point cloud together with additional sensor data captured by a second sensor of the first vehicle; the additional sensor data is captured contemporaneously with the point cloud captured by the LIDAR sensor; and the second sensor is a camera, a radar sensor, or another LIDAR sensor. ### Claim 17 (depends on 16) The system of claim 16, wherein the second sensor is a camera, and wherein to generate a bounding box around each detected object, the one or more processors are configured to: determine two-dimensional boundaries of objects in an image captured by the camera; and map the two-dimensional boundaries to corresponding regions of the point cloud to form three-dimensional bounding boxes around points in the point cloud. ### Claim 18 (depends on 11) The system of claim 11, wherein to filter the input map, the one or more processors are configured to: perform a first filtering operation in which features corresponding to ground reflections and moving objects are removed from the input map, the moving objects being removed through point motion classification; and perform a second filtering operation after the first filtering operation, the second filtering operation removing features that have been assigned a class label corresponding to the at least one object class. ### Claim 19 (depends on 11) The system of claim 11, wherein the filtered map is transmitted to the second vehicle through a wireless connection while the second vehicle is traveling along the same route, and wherein the navigation system of the second vehicle is configured to determine the location of the second vehicle through matching features included in the filtered map to corresponding features in sensor data captured by a sensor of the second vehicle. ### Claim 20 A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors of a computer system, cause the one or more processors to perform the following: generating, based on sensor data captured by a first sensor of a first vehicle, an input map corresponding to a three-dimensional representation of a route traveled by the first vehicle; detecting, by the computer system, objects represented in the sensor data, wherein the detecting comprises assigning a corresponding class label to features associated with the same object, each class label being selected from a set of predefined object classes; generating, by the computer system, a bounding box around each detected object; filtering, based on one or more criteria, the input map to generate a filtered map, wherein: the filtering comprises automatically removing features that satisfy the one or more criteria, the one or more criteria identify objects that are irrelevant to determining a location of a second vehicle with reference to the filtered map, and the one or more criteria comprise at least one object class such that at least some features are removed based on having been assigned a class label corresponding to the at least one object class and further based on belonging to the same bounding box; and transmitting the filtered map to the second vehicle, wherein the filtered map is usable by a navigation system of the second vehicle to determine a location of the second vehicle while the second vehicle is traveling along the same route.