# US 11,079,235 B2 · Method for accelerometer-assisted navigation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,079,235 B2 - Document ID: US11079235B2 - Status: Granted - Kind: B2 - Application number: 16/240,183 - Filed: 2019-01-04 - Published: 2019-05-09 - Granted: 2021-08-03 - Earliest claimed: 2015-08-20 - Assignees: Zendrive, Inc. - Applicants: Zendrive, Inc. - Inventors: Romit Roy Choudhury; Jayanta Pal; Pankaj Risbood; Jonathan Matus - Web page: https://patentgrep.com/patent/US11079235B2 ## CPC - G01C 21/165: {combined with non-inertial navigation instruments} - G01C 21/30: Map- or contour-matching - 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) ## Abstract A method for primarily sensor-based navigation includes: in a first time period, collecting geophysical position data using a GPS receiver of a navigation device; in the first time period, collecting a first set of accelerometer data using an accelerometer of the navigation device; analyzing the first set of accelerometer data to produce a first set of vertical vehicular motion data; generating a mapping association between the first set of vertical vehicular motion data and the geophysical position data; in a second time period after the first time period, collecting a second set of accelerometer data using the accelerometer; analyzing the second set of accelerometer data to produce a second set of vertical vehicular motion data; and calculating an estimated location of the vehicle by analyzing the second set of vertical vehicular motion data in light of the mapping association. ## Claims ### Claim 1 A method for navigation of a vehicle on a road surface, the method comprising: in a first time period, collecting geographic position data using a location sensor of a navigation device; in the first time period, collecting a first set of inertial data using an inertial sensor of the navigation device; analyzing the first set of inertial data to generate a first set of vertical vehicular motion data; generating a mapping association between the first set of vertical vehicular motion data and the geographic position data; in a second time period after the first time period, collecting a second set of inertial data using the inertial sensor; analyzing the second set of inertial data to generate a second set of vertical vehicular motion data; calculating an estimated location of the vehicle based on the second set of vertical vehicular motion data and the mapping association; and switching off the location sensor of the navigation device based on the estimated location of the vehicle. ### Claim 2 (depends on 1) The method of claim 1, wherein the location sensor comprises a GPS receiver, and wherein the inertial sensor comprises an inertial measurement unit (IMU). ### Claim 3 (depends on 1) The method of claim 1, wherein vertical vehicular motion data describes motion of the vehicle perpendicular the road surface. ### Claim 4 (depends on 1) The method of claim 1, further comprising: determining a set of previously traveled routes, each previously traveled route of the set of previously traveled routes associated with geographic positions previously mapped to vertical vehicular motion data; receiving, at the navigation device, a travel source and a travel destination; determining that a first previously traveled route from the set of previously traveled routes intersects the travel source, the travel destination, and the estimated location of the vehicle; and navigating the vehicle according to the first previously traveled route. ### Claim 5 (depends on 4) The method of claim 4, wherein navigating the vehicle according to the first previously traveled route comprises navigating based on vertical vehicular motion data without collecting additional geographic position data. ### Claim 6 (depends on 4) The method of claim 4, wherein navigating the vehicle according to the first previously traveled route comprises navigating based on vertical vehicular motion data without collecting additional geographic position data. ### Claim 7 (depends on 1) The method of claim 1, further comprising: in the first time period, collecting a first vehicle suspension profile; in the second time period, collecting a second vehicle suspension profile; wherein determining the estimated location of the vehicle comprises analyzing the second set of vertical vehicular motion data based on: the mapping association, the first vehicle suspension profile, and the second vehicle suspension profile. ### Claim 8 (depends on 1) The method of claim 1, wherein analyzing the second set of inertial data to produce the second set of vertical vehicular motion data comprises calibrating the second set of vertical vehicular motion data with suspension calibration data. ### Claim 9 (depends on 8) The method of claim 8, wherein calibrating the second set of vertical vehicular motion data with suspension calibration data comprises generating suspension calibration data based solely on analyzing the second set of inertial data. ### Claim 10 (depends on 8) The method of claim 8, wherein calibrating the second set of vertical vehicular motion data with suspension calibration data comprises generating suspension calibration data by: collecting a second set of geographic position data received by the location sensor in the second time period; deriving a location-sensor-derived location based on the second set of geographic position data; generating a reference vertical vehicular motion profile from the mapping association and the location-sensor-derived location; and comparing the reference vertical vehicular motion profile to the second set of inertial data. ### Claim 11 (depends on 8) The method of claim 8, wherein calibrating the second set of vertical vehicular motion data with suspension calibration data comprises detecting a vehicle type with the navigation device and generating suspension calibration data based on the vehicle type. ### Claim 12 A method for navigation of a vehicle, the method comprising: receiving a mapping association between a first set of vertical vehicular motion data and a set of geographic position data; after receiving the mapping association, collecting a set of inertial data; analyzing the set of inertial data to produce a second set of vertical vehicular motion data; and determining an estimated location of the vehicle based on the second set of vertical vehicular motion data and the mapping association; and switching off a location sensor of the navigation device based on the estimated location of the vehicle. ### Claim 13 (depends on 12) The method of claim 12, further comprising determining a set of vehicle suspension calibration data, wherein determining the estimated location comprises analyzing the second set of vertical vehicular motion data based on the mapping association and the set of vehicle suspension calibration data. ### Claim 14 (depends on 13) The method of claim 13, wherein the set of inertial data is collected during a time period, wherein determining the set of vehicle suspension calibration data comprises: collecting the set of geographic position data at a location sensor of a navigation device during the time period; deriving a location-sensor-derived location based on the set of geographic position data; generating a reference vertical vehicular motion profile from the mapping association and the location-sensor-derived location; determining a comparison between the reference vertical vehicular motion profile and the set of inertial data; and generating the set of vehicle suspension calibration data based on the comparison. ### Claim 15 (depends on 12) The method of claim 12, wherein the set of inertial data is collected at an inertial sensor of a navigation device, and further comprising, at the navigation device, detecting a vehicle type of the vehicle, wherein the set of vehicle suspension calibration data is determined based on the vehicle type. ### Claim 16 (depends on 15) The method of claim 15, wherein detecting the vehicle type comprises extracting a vehicle signature from a communication link between the navigation device and the vehicle. ### Claim 17 (depends on 12) The method of claim 12, further comprising: determining a set of previously traveled routes, each previously traveled route of the set of previously traveled routes associated with geographic positions previously mapped to vertical vehicular motion data; receiving a travel source and a travel destination; determining that a first previously traveled route from the set of previously traveled routes defines a travel frequency above a threshold value. ### Claim 18 (depends on 17) The method of claim 17, wherein the set of inertial data is collected at an inertial measurement unit of a navigation device, the method further comprising: determining a location estimate error. ### Claim 19 (depends on 12) The method of claim 12, further comprising, before collecting the set of inertial data: in a time period, collecting the set of geographic position data using a GPS receiver of a navigation device; in the time period, collecting a prior set of inertial data using an inertial measurement unit (IMU) of the navigation device; analyzing the prior set of inertial data to produce the first set of vertical vehicular motion data; and generating the mapping association based on the first set of vertical vehicular motion data and the set of geographic position data.