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WO2016018170A1 - Localisation d'un objet mobile en utilisant un système de mesure inertielle - Google Patents

Localisation d'un objet mobile en utilisant un système de mesure inertielle Download PDF

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Publication number
WO2016018170A1
WO2016018170A1 PCT/RU2014/000573 RU2014000573W WO2016018170A1 WO 2016018170 A1 WO2016018170 A1 WO 2016018170A1 RU 2014000573 W RU2014000573 W RU 2014000573W WO 2016018170 A1 WO2016018170 A1 WO 2016018170A1
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WO
WIPO (PCT)
Prior art keywords
motion
motion pattern
predefined
pat1
location
Prior art date
Application number
PCT/RU2014/000573
Other languages
English (en)
Inventor
Artem Vladimirovich OZHIGIN
Original Assignee
Siemens Aktiengesellschaft
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens Aktiengesellschaft filed Critical Siemens Aktiengesellschaft
Priority to PCT/RU2014/000573 priority Critical patent/WO2016018170A1/fr
Publication of WO2016018170A1 publication Critical patent/WO2016018170A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation

Definitions

  • the invention relates to a method for localizing a movable object, like e.g. a vehicle or a mobile phone.
  • the localization is performed on the basis of a motion signal as it is provided by an inertial measurement unit that may comprise e.g. an accelerometer and/or a gyroscope.
  • the invention also provides a mobile device designed for performing the inventive method.
  • Localizing a movable device i.e. determining the current device location or device position, may be performed on the basis of a measurement of the acceleration and/or changes in spatial orientation.
  • the information about acceleration of the device In order to obtain an estimate of the current device location, the information about acceleration of the device must be summed up or mathematically integrated twice to obtain first velocity and then position. Thus, over time small measurement errors that come with each measurement of acceleration or angular rate may accumulate and result in a progressive drift of the estimate with regard to the real device location.
  • Locating or localizing movable devices on the basis of a motion signal from an inertial measurement unit is especially attractive in cases, where global satellite- based positioning systems do not operate, as it is the case inside buildings due to signal attenuation by building constructions.
  • dedicated systems based on different wireless technologies using electromagnetic waves may be deployed in the building to provide location services. However, they require a specific hardware .
  • inertial measurement units based on accelerometers and/or gyroscopes are available in general purpose hardware like mobile phones or tablet PCs, it is difficult to use their motion signal for localizing a movable device due to the integration drift caused by continuous accumulation of measurement errors resulting from the numerical integration of angular rate and accelerations.
  • the localization of the mobile or movable device or object is based on an inertial measurement unit that is provided with the device.
  • the method comprises the step of receiving the motion signal from the inertial measurement unit.
  • the inertial measurement unit generates its motion signal in dependence on motions of the device which may be a velocity and/or an acceleration and/or an angular velocity or angular rate.
  • the inventive method further comprises the step of generating a measured motion pattern based on the motion signal.
  • the motion signal is used to estimate several device locations or positions over time and combine those estimates to give a motion path that forms the motion pattern.
  • the inventive method is characterized by the following steps: At least one predefined motion pattern is provided, i.e. a hypothetical or theoretical motion pattern that might be generated by the movable device. Together with each predefined motion pattern, location data are provided that describe a known location. All combinations of a predefined motion pattern and the corresponding location data together form a motion pattern set. It is now possible to compare the measured motion pattern describing the real motion path that the movable device has moved along, with all the predefined motion patterns comprised in the motion pattern set.
  • the method comprises the step of finding in the motion pattern set a predefined motion pattern that matches the measured motion pattern according to a predefined matching criterion.
  • the matching criterion may provide a predefined flexibility or tolerance in order to identify a matching predefined motion pattern, although the patterns do not match exactly.
  • Once a matching predefined motion pattern is found the location data associated with that matching predefined motion pattern may be used as a description of the current device location.
  • a description of the device location is provided that is not only based on the motion signal itself, but also on the predefined locations described by the location data stored in the motion pattern set.
  • the inventive method provides a significant increase in accuracy of localizing a movable device on the basis of a motion signal generated by an inertial measurement unit.
  • a further advantage is that the method works without additional infrastructure. It may rely exclusively on the inertial measurement unit and a processing unit that provides the motion pattern set and performs the search or comparison of the measured motion pattern with the predefined motion patterns in the motion pattern set. This makes it possible to perform the localization based on the hardware of general purpose devices which are already on the market, thus opening the application of localization to a wide range of technical devices like mobile phones, portable and hand-held PCs, robots and/or vehicles. Also, low-cost and simple hardware may be provided for embedded positioning devices for manned and robotic vehicles.
  • the motion signal comprises the sensor signal of at least one accelerometer and/or at least one gyroscope.
  • the inertial measurement unit has at least three accelerometers to measure acceleration along vertical, longitudinal and latitudinal axis.
  • the inertial measurement unit may comprise up to three gyroscopes to measure angular rates.
  • sensor signals of accelerometers and/or gyroscopes provides the advantage that the sensors can be completely enclosed in a casing and do not depend on the measurement of external signals. In contrast to this, directly measuring, e.g. a velocity of the device, requires measuring a movement of an element, e.g. a wheel. Such sensors are sensitive to deterioration, erosion or dirt. Accelerometers and gyroscopes may be designed much more robust with regard to deterioration.
  • one embodiment of the method comprises the step of estimating a current device location in dependence on the motion signal itself.
  • the known method of estimating the current device location by integration may also be comprised in the inventive method.
  • this embodiment further comprises the step of calculating a respective distance to each location described by the location data in the motion pattern set. In other words, it is determined how far the current estimated location is away from any of the predefined known locations that are described by the location data.
  • the term "distance" may relate to the direct geometrical distance. The distance may also consider obstacles like walls, i.e.
  • the distance may be a path length calculated along possible motion paths that may be followed by the movable device.
  • those motion pattern/location data combinations from the motion pattern set are selected that comprise location data of a location in a predefined vicinity of the current device location.
  • the vicinity may be defined as a maximum distance value.
  • only those combinations of predefined motion pattern/location data are considered that belong to a location whose relative distance to the current device location is smaller than the maximum distance value.
  • the selected combinations are used for matching the measured motion pattern with the predefined motion patterns. This allows to speed up the process of finding the matching predefined motion pattern.
  • a complex and/or resource-demanding method for performing the pattern-matching may be employed.
  • Another embodiment of the invention comprises repeating the two steps of finding the matching predefined motion pattern and providing the location data in periodic intervals and/or at predefined points in time. This ensures a regular re-calibration of the localization.
  • the repetition may also be triggered in response to a trigger signal of a sensor or of an observation unit.
  • a trigger sensor may be, e.g., a touch screen of a mobile phone such that the localization is re-calibrated whenever the user of the mobile phone begins using his phone.
  • An observation unit may be, e.g., a central computer for observing the locations of several movable devices, like robots in a warehouse, wherein the central computer performs an update of a list of the locations of each movable device.
  • the embodiment comprises the step of providing a map of a predefined area, e.g., a warehouse or an office.
  • the map comprises data of possible motion paths of the device in the area.
  • Such data may comprise a description of the building construction, e.g., the positions of walls and other hindering objects, and/or the course of free corridors.
  • the embodiment further comprises a step of defining the at least one combination of a predefined motion pattern and location data based on the data of the map.
  • Such characteristic patterns may include narrow turns, long straight passages, a passage through partitions via, e.g., doors .
  • one embodiment of the inventive method comprises the step of providing the predefined motion pattern for at least one of the following motion paths: vertical ascend and/or vertical descend, especially of an elevator, escalator, a ladder, staircases. These motion paths provide especially characteristic motion patterns that may be easily distinguished from horizontal motions.
  • one embodiment of the method comprises the step of finding the matching predefined motion pattern on the basis of a clustering method and/or a Bayesian network, especially a hidden Markov model.
  • the coordinates describing the measured motion pattern may be aligned to form one vector that describes a point in a multi-dimensional mathematical space. This mathematical space may be sub-divided into regions, wherein each region represents one predefined motion pattern.
  • a Bayesian network, especially a hidden Markov model may be trained by means of measurement data generated from recorded motion signals.
  • the matching criterion may be a predefined minimum value for the confidence, i.e. a minimum likelihood value that must be reached or topped.
  • the inventive method may also be flexibly combined with additional sensors.
  • One embodiment comprises the step of receiving a sensor signal of at least one sensor outside the inertial measurement unit, especially a light sensitive sensor and/or a sensor of velocity and/or a clock. Finding the matching motion pattern in the motion pattern set is then also based on the respective additional sensor signal.
  • the additional sensor signal of the additional sensor may be used to verify whether a certain match is plausible. For example, if an ascend of the mobile movable device is detected on the basis of the motion signal of the inertial measurement unit, the movable device may be inside an elevator moving upwards. However, if - at the same time - the additional sensor signals a forward motion it is very unlikely that the movable device is inside the cabin of an elevator.
  • Using a light sensitive sensor may, e.g., provide the information whether the movable device is inside or outside a certain place like a building or a pocket. On the basis of a clock signal, it may be verified whether it is very likely that the movable device is within a certain location. If the location is not accessible a certain time, like, e.g., a supermarket during night, this location may be ruled out .
  • the invention also provides a mobile device comprising an inertial measurement unit of the type already described.
  • the mobile device also provides a processing unit coupled to the inertial measurement unit.
  • the inventive mobile device is characterized in that the processing unit is designed to receive the motion signal of the inertial measurement unit and perform an embodiment of the inventive method .
  • the mobile device may be a robot, a fork lift, a mobile phone, a hand-held PC, a vehicle, like, e.g., a car, or a wearable device, like a bracelet or a jacket.
  • a further aspect of the invention is concerned with a tangible data storage medium.
  • the inventive storage medium comprises a program code executable by a processing unit of a mobile device, wherein the program code is designed to perform an embodiment of the inventive method, when executed by the processing unit.
  • the tangible data storage medium according to the invention provides the advantage that existing mobile devices, like mobile phones or handheld PCs or robots, may be equipped with program code to perform an embodiment of the inventive method.
  • the accompanying drawing illustrates the embodiment.
  • the figure shows a mobile device 10 comprising an inertial measurement unit 12, a location estimator 14, and a correction unit 16.
  • the mobile device can be a vehicle, like a ground conveyor or a fork lift, an autonomously moving robot, a hand-held device, like a smartphone or a hand-held PC, or a wearable device, like a jacket.
  • the inertial measurement unit 12 can comprise accelerometers 18, 20, 22, wherein the accelerometers 18, 20, 22 may be configured to measure acceleration along different axes:
  • the accelerometer 18 may be configured to measure along a vertical axis
  • the accelerometer 20 may be configured to measure along a longitudinal axis
  • the accelerometer 22 may be configured to measure along a latitudinal axis.
  • the inertial measurement unit may comprise more than or less than the shown three accelerometers 18, 20, 22.
  • the inertial measurement unit may comprise gyroscopes 24, 26, 28 to measure angular rates in different planes.
  • the inertial measurement unit may comprise more than or less than the shown three gyroscopes 24, 26, 28.
  • Each of the sensors 18 to 28 may be provided as a electronic device, e.g. an MEMS (micro electro-mechanical system).
  • MEMS micro electro-mechanical system
  • the sensor signals of the accelerometers 18, 20, 22 and/or the gyroscopes 24, 26, 28 may together form a motion signal S that is provided to the localization module 14.
  • the localization module 14 may be designed to estimate a current device location XYZ on the basis of the motion signal S.
  • the localization module 14 may be a program module executed by a processing unit of the mobile device 12.
  • the estimation of the current device location XYZ may be based on a double integration in order to estimate a current velocity VXYZ based on the first accumulation or integration 30 and then to estimate the location XYZ based on a second accumulation or integration 32.
  • the mobile device 10 may be part of an application foreseen in a warehouse management, a guided tour, a mall, an airport, or a store.
  • the indoor positioning or localization may be performed wirelessly on the basis of the estimate of the device location XYZ.
  • the estimated device location XYZ may comprise a progressive drift that can guickly cause inacceptable positioning error.
  • the device 10 does not have this problem.
  • the estimated device location XYZ may be corrected by the correction unit 16 to give a corrected device location XYZcorr.
  • the correction unit 16 may be another program module executed by the processing unit of the mobile device 10.
  • the correction unit 16 may comprise a pattern generator 34, a map 36, a motion pattern set 38, and a pattern matcher 14.
  • the pattern generator 34 may receive several successive estimated device locations XYZ from the location estimator 14 and may combine these estimates to generate a motion path 42 describing the path along which the mobile device 10 has moved within a predefined amount of time, wherein the amount of time may be in the interval from one second to one hour, for example.
  • the motion path 42 or a section or part of it may be transmitted to the pattern matcher 40 as a measured motion pattern PAT.
  • the motion pattern set 38 may comprise a list of pairs or combinations 44, wherein each combination 44 comprises a predefined motion pattern PAT1 to PAT6 together with corresponding or associated location data describing a known predefined location XYZl to XYZ6.
  • the predefined motion patterns PAT1 to PAT6 and/or the locations XYZl to XYZ6 may be derived from map 36.
  • the predefined motion patterns PAT1 to PAT6 may describe the following motion paths (in this order) : a double turn, a loop, a motion along a long passage, an ascend, a descend, a U-turn. In the figure, corresponding symbols are shown.
  • the predefined location XYZl to XYZ6 is visualized in the corresponding pattern PAT1 to PAT 6 by a cross x.
  • the map 36 may describe an area in which the mobile device 10 is to be localized.
  • the area may comprise two floors FLOOR0, FLOOR1 of a building.
  • the two floors FLOOR0 and FLOOR1 may be connected by an escalator 46.
  • the map 36 may also comprise data describing walls 48 of the buildings. From the map 38 possible motion patterns could be derived as the predefined motion patterns PAT1 to PAT6.
  • the matching unit 40 may be designed to compare the measured motion pattern PAT with one or more or all of the predefined motion patterns PAT1 to PAT6 of the pattern motion set 38.
  • the comparison may be based on, e.g., a clustering method and/or a Bayesian estimator method, like a hidden Markov model.
  • the matching unit 40 may first select a sub-set from the pattern motion set 38. This may be performed by first checking where in the map 38 the estimated device location XYZ is positioned. In the visualized example the estimated device location XYZ points to a position on FLOOR1. The matching unit 40 may then find all those predefined locations XYZl to XYZ6 that lie within ' a predefined vicinity 50.
  • the vicinity 50 may be defined as a circle with radius 52 around the estimated device location XYZ. In the example only the predefined locations XYZl and XYZ2 lie within the vicinity 50.
  • the matching unit 40 may therefore select only the combinations 44 comprising the two predefined XYZl and XYZ2 for the pattern matching.
  • the motion path 44 i.e. the measured motion pattern PAT matches the predefined pattern PAT1.
  • the matching unit 40 may therefore output the predefined location XYZl as the corrected device location XYZcorr .
  • the predefined patterns PAT1 to PAT6 may also comprise additional data, for example velocity data describing the motion velocity that was observed while the mobile device 10 moved along the motion path forming the corresponding motion patterns PAT1 to PAT6.
  • additional data for example velocity data describing the motion velocity that was observed while the mobile device 10 moved along the motion path forming the corresponding motion patterns PAT1 to PAT6.
  • the estimated velocity VXYZ may be used or a measured velocity provided by an additional sensor.
  • the corrected device location XYZcorr may be used to provide localization information of the mobile device 10, i.e. an object like a robot or a vehicle, or a person carrying the mobile device 10.
  • the localization estimator 14 and the correction unit 16 are preferably provided in connection with an indoor positioning system (IPS) .
  • IPS indoor positioning system
  • Such a system then does not require any external infrastructure and can be realized as a system embedded into vehicle (a fork lift or another transport vehicle) or a person vehicle, or as a hand-held device or wearable device or even purely software solution in a general purpose device like a mobile phone or a handheld PC of any kind.
  • IPS indoor positioning system
  • the indoor positioning system shall preferably have a spatial map 36 of the building. In this map 36 there shall be introduced characteristic motion patterns for certain locations XYZ1 to XYZ2 within the building.
  • the system Every time the system detects an actual motion pattern PAT matching one pattern PAT1 to PAT6 stored in the map 36 in some vicinity 50 of the current calculated location XYZ, it can automatically compensate accumulated error by immediate fixation to the proper map location XYZ1 to XYZ6.
  • Such characteristic patterns may include narrow turns, long straight passages, vertical ascends and descends in elevators, escalators, ladders and staircases; a passage through partitions via doors or similar.
  • the example illustrates how the invention provides an inertial indoor positioning system with error correction.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Navigation (AREA)

Abstract

L'invention concerne la localisation d'un dispositif mobile, par exemple, un véhicule ou un téléphone mobile. L'invention fournit un procédé comprenant les étapes consistant à recevoir un signal de mouvement (S) à partir d'une unité de mesure inertielle (12) du dispositif (10) et à générer un modèle de mouvement mesuré (PAT) sur la base du signal de mouvement (S). L'objet de l'invention est de fournir une localisation précise. À cette fin, le procédé de l'invention comprend en outre l'étape supplémentaire consistant à fournir un ensemble de modèles de mouvement (38) comprenant au moins une combinaison (44) d'un modèle de mouvement prédéfini (PAT1 à PAT6) et de données de localisation décrivant un emplacement (XYZ1 à XYZ6) ; et l'étape consistant à trouver dans l'ensemble de modèles de mouvement (38) un modèle de mouvement prédéfini (PAT1) qui correspond au modèle de mouvement mesuré (PAT) selon un critère de correspondance prédéfini ; et l'étape consistant à fournir les données de localisation associées au modèle de mouvement prédéfini correspondant (PAT1).
PCT/RU2014/000573 2014-07-30 2014-07-30 Localisation d'un objet mobile en utilisant un système de mesure inertielle WO2016018170A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/RU2014/000573 WO2016018170A1 (fr) 2014-07-30 2014-07-30 Localisation d'un objet mobile en utilisant un système de mesure inertielle

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Application Number Priority Date Filing Date Title
PCT/RU2014/000573 WO2016018170A1 (fr) 2014-07-30 2014-07-30 Localisation d'un objet mobile en utilisant un système de mesure inertielle

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11546724B2 (en) 2020-08-12 2023-01-03 Here Global B.V. Method, apparatus, and system for determining a non-specific location according to an observed mobility pattern derived from non-positioning related sensor data

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014016602A1 (fr) * 2012-07-24 2014-01-30 Sensewhere Limited Procédé d'estimation de position de dispositif
US20140187258A1 (en) * 2012-12-31 2014-07-03 Qualcomm Incorporated Context-based parameter maps for position determination

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014016602A1 (fr) * 2012-07-24 2014-01-30 Sensewhere Limited Procédé d'estimation de position de dispositif
US20140187258A1 (en) * 2012-12-31 2014-07-03 Qualcomm Incorporated Context-based parameter maps for position determination

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11546724B2 (en) 2020-08-12 2023-01-03 Here Global B.V. Method, apparatus, and system for determining a non-specific location according to an observed mobility pattern derived from non-positioning related sensor data

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