# US 2018/0321353 A1 · System and method for automating beacon location map generation using sensor fusion and simultaneous localization and mapping > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0321353 A1 - Document ID: US20180321353A1 - Status: Published application - Kind: A1 - Application number: 15/586,234 - Filed: 2017-05-03 - Published: 2018-11-08 - Earliest claimed: 2017-05-03 - Assignees: Fuji Xerox Co., Ltd. - Applicants: Fuji Xerox Co., Ltd. - Inventors: Miteshkumar Patel; Maani Ghaffari Jadidi; Jacob Biehl; Andreas Girgensohn - Web page: https://patentgrep.com/patent/US20180321353A1 ## CPC - G01S 5/04: Position of source determined by a plurality of spaced direction-finders - G01C 21/1654: {with electromagnetic compass} - G01C 21/206: {specially adapted for indoor navigation} - H04W 4/02: Services making use of location information - H04W 4/029: Location-based management or tracking services - H04W 4/80: Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication - G09B 29/10: Map spot or coordinate position indicators; Map reading aids (optical projection apparatus per se G03B) - 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 - 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) - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) - G09B: EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS (devices for psychotechnics or for testing reaction times A61B5/16; games, sports, amusements A63; projectors, projector screens G03B) ## Abstract A system and method, which utilizes incremental smoothing and mapping (iSAM) algorithm and automatically builds a beacon location map using various sensor and environmental information. The aforesaid iSAM algorithm fuses received signal strength indicator (RSSI) values available from different beacons in the environment and the information provided by the IMU sensor. The aforesaid iSAM algorithm is capable of simultaneously generating beacon and landmark map and localize the mobile computing device in the environment without having any prior information about any beacon locations. To accommodate for noisy sensor data and achieve better convergence for the iSAM algorithm, the system uses a prior beacon location map, which contains location information of some of the BLE beacons located in the environment. These known beacon locations provide cleaner environmental information to the iSAM algorithm and hence improve the overall estimation of beacon locations, which were not available apriori. ## Claims ### Claim 1 A computer-implemented method, the method being performed in a computerized system comprising a central processing unit, a localization signal receiver, a plurality of sensors, separate and distinct from the localization signal receiver, and a memory, the computer-implemented method comprising: a. receiving a plurality of localization signals corresponding to a plurality of localization signal sources using the localization signal receiver; b. obtaining a plurality of sensor readings using the plurality of sensors; and c. determining a location of each of the plurality of localization signal sources based on the received localization signal and the obtained plurality of sensor readings. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the localization signal receiver is a Bluetooth receiver and wherein the localization signal sources are Bluetooth low energy (BLE) beacons. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the localization signal receiver is a radiofrequency receiver and wherein the localization signal sources are radiofrequency sources. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein determining the location of each of the plurality of localization signal sources comprises dynamically updating the location of each of the plurality of localization signal sources using an iterative smoothing and mapping algorithm (iSAM). ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein determining the location of each of the plurality of localization signal sources comprises generating a smoothened trajectory data. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein the plurality of sensor readings comprises magnetometer data. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein the plurality of sensor readings comprises acceleration data. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the plurality of sensor readings comprises a three-dimensional spatial orientation data. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, further comprising calculating an orientation of the computerized system using an attitude and heading reference system (AHRS) algorithm performed on at least some of the plurality of sensor readings. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein the plurality of sensors are incorporated into an inertial measurement unit (IMU). ### Claim 11 (depends on 1) The computer-implemented method of claim 1, wherein determining the location of each of the plurality of localization signal sources comprises continuously executing a particle filter and continuously dynamically updating bias parameters for the plurality of sensors and the location of each of the plurality of localization signal sources. ### Claim 12 (depends on 11) The computer-implemented method of claim 11, wherein continuously executing the particle filter comprises performing a motion update, performing a measurement update and resampling a plurality of particles. ### Claim 13 (depends on 12) The computer-implemented method of claim 12, wherein performing the measurement update comprises calculating a distance between each of a plurality of particles and at least one localization signal source based on the received localization signal. ### Claim 14 (depends on 12) The computer-implemented method of claim 12, wherein performing the measurement update comprises updating a plurality of particles using a confidence of a classifier. ### Claim 15 (depends on 12) The computer-implemented method of claim 12, wherein resampling the plurality of particles comprises calculating a weight for each of a plurality of particles and replicating particles of the plurality of particles with higher weights. ### Claim 16 (depends on 1) The computer-implemented method of claim 1, wherein determining the location of each of the plurality of localization signal sources comprises using prior information on locations of at least some of the plurality of localization signal sources. ### Claim 17 A non-transitory computer-readable medium embodying a set of computer-executable instructions, which, when executed in connection with a system comprising a central processing unit, a Bluetooth localization signal receiver, a plurality of sensors, separate and distinct from the Bluetooth localization signal receiver, and a memory, cause the system to perform a method comprising: a. receiving a plurality of localization signals corresponding to a plurality of localization signal sources using the localization signal receiver; b. obtaining a plurality of sensor readings using the plurality of sensors; and c. determining a location of each of the plurality of localization signal sources based on the received localization signal and the obtained plurality of sensor readings. ### Claim 18 A computerized system comprising a central processing unit, a Bluetooth localization signal receiver, a plurality of sensors, separate and distinct from the Bluetooth localization signal receiver, and a memory, the memory storing a set of computer-readable instructions causing the system to perform a method comprising: a. receiving a plurality of localization signals corresponding to a plurality of localization signal sources using the localization signal receiver; b. obtaining a plurality of sensor readings using the plurality of sensors; and c. determining a location of each of the plurality of localization signal sources based on the received localization signal and the obtained plurality of sensor readings. ### Claim 19 (depends on 18) The computerized system of claim 18, wherein the localization signal receiver is a Bluetooth receiver and wherein the localization signal sources are Bluetooth low energy (BLE) beacons. ### Claim 20 (depends on 18) The computerized system of claim 18, wherein the localization signal receiver is a radiofrequency receiver and wherein the localization signal sources are radiofrequency sources.