WO2006086398A2 - Systeme de poursuite de position - Google Patents

Systeme de poursuite de position Download PDF

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Publication number
WO2006086398A2
WO2006086398A2 PCT/US2006/004313 US2006004313W WO2006086398A2 WO 2006086398 A2 WO2006086398 A2 WO 2006086398A2 US 2006004313 W US2006004313 W US 2006004313W WO 2006086398 A2 WO2006086398 A2 WO 2006086398A2
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WO
WIPO (PCT)
Prior art keywords
mobile object
location
tracking device
time
vehicle
Prior art date
Application number
PCT/US2006/004313
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English (en)
Other versions
WO2006086398A3 (fr
Inventor
Aleks GÖLLÜ
Meng-Hsiung Kiang
Original Assignee
Pinc Solutions
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
Priority claimed from US11/054,881 external-priority patent/US7236091B2/en
Priority claimed from US11/054,905 external-priority patent/US7245215B2/en
Priority claimed from US11/175,081 external-priority patent/US7321305B2/en
Application filed by Pinc Solutions filed Critical Pinc Solutions
Publication of WO2006086398A2 publication Critical patent/WO2006086398A2/fr
Publication of WO2006086398A3 publication Critical patent/WO2006086398A3/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
    • G01C21/16—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 by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/183—Compensation of inertial measurements, e.g. for temperature effects
    • G01C21/188—Compensation of inertial measurements, e.g. for temperature effects for accumulated errors, e.g. by coupling inertial systems with absolute positioning systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0257—Hybrid positioning
    • G01S5/0263—Hybrid positioning by combining or switching between positions derived from two or more separate positioning systems
    • G01S5/0264—Hybrid positioning by combining or switching between positions derived from two or more separate positioning systems at least one of the systems being a non-radio wave positioning system
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
    • G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W60/00—Affiliation to network, e.g. registration; Terminating affiliation with the network, e.g. de-registration
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Definitions

  • Position-tracking systems seek to identity the location of mobile objects in real- time and are used in a wide variety of applications, including transportation, logistics management, healthcare, security, etc. Position-tracking systems that can provide continuous location information are desirable for applications that require non-interrupted visibility of the mobile object through a journey. For objects that are moved with a vehicle (such as inter-modal shipping containers or trailers), being able to locate the position of the objects in real-time can help improve the efficiency of supply-chain and inventory management while reducing the loss in productivity of assets. As businesses increasingly depend on a global supply chain and distribution networks, more goods and assets are being moved around for longer distances and with more parties involved in the process. In order to facilitate an automated, error-free data exchange for logistics management, the availability of continuous information about these assets in real-time is more valuable than "discrete" information that is only available for certain regions, albeit with perhaps higher position resolution.
  • GPS Global Positioning System
  • GPS-like technologies with more and more sophisticated software implementations
  • GPS systems are still generally ineffective and unreliable for location tracking indoors or in other environments where obstructions to the satellite signals present challenges.
  • other non-GPS based position technologies that have been proposed to date are largely based on a "local GPS" system using an assembly of locally deployed wireless antennas to mimic the function of the GPS satellites.
  • the present invention is directed to a position-tracking system for tracking the position of an object.
  • the tracking system includes a tracking device that is connected to or otherwise affixed to the object to be tracked.
  • the tracking device may be connected to equipment that is used to move the objects to be tracked.
  • the tracking device may include, among other things, an inertial sensor assembly, radio transceivers and a processor.
  • the position tracking system may also include a host processing system that is in communication with the tracking device.
  • the position tracking system may provide variable-resolution position information based on the environment in which the object is moving.
  • the system may compute a general position for the object based on a wireless telephone network CeIl- ID/map correlation architecture. That is, the system may utilize Cell-ID information obtained from a wireless telephone network in conjunction with a database of area maps to determine a general position of the object (e.g., within the geographic area covered by a certain Cell-ID). In this case, the position tracking system is said to operate in the "wide area" mode.
  • the position tracking system may transition to a corresponding high-resolution mode.
  • the mode transition may be activated, for example, by a wireless activation signal provided at the ingress of the high-resolution area.
  • the greater position resolution may be realized using other wireless signals, from a wireless aiding system within the high-resolution environment, combined with the inputs from the inertial sensors.
  • the tracking system e.g., at either the tracking device, the host processing system, or distributed between these components
  • the combined implementation can provide enhanced accuracy (e.g., on the order of meters) without ever losing coverage of the object, regardless of the layout of the high-resolution environment.
  • the wireless activation signal at the point of egress may deactivate the high-resolution mode and the system may automatically revert back to the wide area mode.
  • the system may exploit distinct patterns of motion that can be identified as motion "signatures" that are characteristic of certain types of motion.
  • the position tracking system may estimate the state of the object (e.g., the heading, position, velocity of the object) based on kinematic models for the current mode of the object.
  • Adaptive and cascaded Kalman filtering or similar techniques may be employed in the analysis to more accurately estimate the position and velocity of the object based on the motion pattern identified.
  • the state history of the object may be stored and used in the state estimate computation to make continuous adjustments to the state estimates in the past.
  • the inertial sensor measurements and a priori estimations for a configurable time period at a configurable frequency may be stored in a data storage device.
  • the a priori estimations may be adjusted to provide more accurate final estimations (with a time delay). For example, when the tracking system determines that the object has become "stationary" based on an identified match to a motion signature, any residual estimated velocity may be corrected (or, smoothed) backwards in time to provide an improved velocity and, hence, position estimations from the original calculation.
  • the host computer system may maintain a centralized, real-time record of the locations of the tracked objects.
  • the record can be stored in a database and/or it may be a direct input to a logistic or other IT management system so that the location information can be further processed or utilized by other applications
  • the present invention is directed to a system that include an object location tracker and a computer system.
  • the object location tracker is configured for attachment to a mobile vehicle and includes an object identification reading device and a position-tracking device.
  • the object identification reading device senses object identification indicia on the object, such as RF ID tags, bar codes, etc., as the mobile vehicle moves around an environment in which the object is situated.
  • the position-tracking device computes the location of the object location tracker as the mobile vehicle moves throughout environment.
  • the computer system associates the sensed object identification indicia of the object, as determined by the reading device, with a location in the environment based on the position of the object location tracker in the environment, as determined by the position-tracking device, when the reading device senses the object identification indicia.
  • the mobile vehicle may include its own mobility system, such as a forklift or an autonomous robotic device, or the mobile vehicle may be, for example, a pushcart that is pushed around the environment. Also, the mobile vehicle may be a person walking around.
  • the present invention is directed to an electronic device comprising an inertial sensor assembly and a processor in communication with the inertial sensor assembly.
  • the processor is programmed to determine an appropriate power level for the processor based on input from then inertial sensor assembly. For example, the processor may be programmed to enter a sleep mode when the processor determines from the input of the inertial sensor assembly that the electronic device had limited movement for a certain period of time.
  • the electronic device may be a position tracking device for use in a position tracking system, or any other electronic device including an on-board processor.
  • Figure 1 is a diagram of a position tracking system for tracking the position of an object according to various embodiments of the present invention
  • FIG. 2 is a block diagram of the tracking device of the system of Figure 1 according to various embodiments of the present invention
  • Figures 3-5 illustrate a process for computing the state estimate of the tracked object according to various embodiments of the present invention
  • Figures 6 and 7 provide an example of how information from the wireless aiding system may be utilized in computing the state estimate of a tracked object according to various embodiments of the present invention
  • Figure 8 is a diagram of the tracking device according to other embodiments of the present invention.
  • Figure 9 illustrates various embodiments of a system for determining a location of an object.
  • FIG. 1 is a diagram of a position-tracking system 10 according to various embodiments of the present invention for tracking the position of one or more mobile objects in real-time (i.e., within a small response time) as the objects travel about.
  • the tracked objects may be any tangible object that is capable of moving, whether by its own mobility system or because it is capable of being transported by other means, such as conveyor belts, vehicles, lifts, persons, etc. Accordingly, the tracked objects may be goods, containers or supports for goods, vehicles or equipment for moving goods, etc. Also, the tracked objects or goods may or may not have RFID tags. That is, the position tracking system described herein may be used in conjunction with RFID technology or in lieu of it.
  • the tracking system 10 tracks the position of the objects as they travel through areas, such as area 12, where very high position location resolution is not needed, and areas, such as area 14, where high position resolution is needed.
  • Area resolution areas may include areas where the objects are in transit between locations such as, for example, intermodal transportation hubs, shipyards, rail yard, etc. In such areas, position resolution on the order of hundreds or thousands of meters may be acceptable.
  • "high resolution” areas whether indoor or outdoor environments, are areas that require more precise location information for logistical purposes, such as on the order of a few meters or less. Examples of high-resolution areas include manufacturing facilities, campuses, warehousing facilities, etc.
  • the position-tracking system 10 may include, according to various embodiments, one or more tracking devices 16 and a host computer system 18 that communicates with the tracking devices 16.
  • the tracking devices 16 may be attached or otherwise connected to the objects to be tracked, for example.
  • three tracking devices 16i -3 are shown, one attached to a truck 22 traveling in the wide-resolution area 12, a second connected to goods on a first forklift 23 1 in the high-resolution area 14, and a third connected to a second forklift itself 23 2 . It should be recognized that the tracking devices 16 could be attached or otherwise connected to other types of vehicles, goods, containers for the goods, equipment, etc.
  • tracking devices could be connected to mobile assets (e.g., goods), such as the tracking device 16 2 in Figure 1, or to equipment (e.g., forklifts) that are used to move mobile assets around a facility, such as the tracking device I6 3 in Figure 1.
  • mobile assets e.g., goods
  • equipment e.g., forklifts
  • tracking the location of equipment for example, the location of object/goods that are not capable of moving by themselves can be effectively tracked in certain applications, as long as information on which object(s) is associated with the tracked equipment at any given time is available.
  • the tracking system 10 may track a greater number of objects than the two shown in Figure 1.
  • the tracking devices 16 preferably include processing capabilities that allow them to estimate their real-time position based on, for example, inertial sensor inputs and wireless signals.
  • the tracking devices 16 may operate in one of two modes ⁇ a wide area mode and a high-resolution mode — and compute their estimated position differently depending on its mode of operation. For example, when a tracking device 16 is in the high-resolution area 14 (such as connected to goods on the forklift 23 ⁇ or connected to the forklift 23 2 itself), the tracking device 16 may correspondingly be in its high-resolution mode and compute its estimated position with an accuracy on the order of a few meters or less based on the input from inertial sensors and wireless signals from a wireless aiding system.
  • the wireless aiding system may include, as shown in Figure 1, one or more reference point transmitters 28 for providing a reference location to the tracking device 16.
  • the tracking device 16 When the tracking device 16 is in the wide resolution area 12 (such as connected to goods or containers on the truck 22), it may correspondingly be in the wide area mode and its estimated position in this mode may have less resolution, such as on the order of hundreds or thousands of meters.
  • Such a dual resolution mode approach may be satisfactory in position tracking applications where highly accurate position information is not needed in the wide resolution areas but is needed in other environments. Indeed, the dual mode approach may be preferable because it does not require the wireless location aiding system for the high-resolution area to be built out in the wide resolution areas.
  • the tracking device 16 may transmit its estimated position to the host computer system 18. This may be done continuously, periodically, randomly, pseudo-randomly, and/or upon a request from the host computer system 18.
  • the host computer system 18 may maintain a centralized, real-time record of the locations of the tracked objects.
  • the record can be stored in a database 24 and/or it may be a direct input to a logistic or other IT management system so that the location information can be further processed or utilized by other applications.
  • the host computer 18 may be implemented as one or a number of networked computers, such as servers, PCs, workstations, etc.
  • the tracking device 16 may compute its estimated position and transmit the position to the host 18, although according to other embodiments, the position determination processing may be distributed between the processing capabilities of the tracking device 16 and the host 18. Also, although only three tracking devices 16 is shown in Figure 1, it should be recognized that at any one time the host computer system 18 may be in communication with a fewer or greater number of tracking devices. Further, the host computer system 18 may control and monitor the tracking devices 16 via control and monitoring signals sent to the tracking devices 16.
  • the wireless aiding system used in the high-resolution area 14 may include a number of reference point transmitters 28 positioned throughout the high-resolution area 14. Each reference point transmitter 28 may wirelessly transmit a high accurately reference location position to the tracking devices 16, such as with RF, acoustic, optical, IR or other suitable signals, such that the tracking devices 16 can compute their position based on the reference as well as with input from inertial sensors, as described in more detail below.
  • the high-resolution areas 14 may also include a number of radio access points 30.
  • the radio access points 30 may provide a wireless gateway (e.g., via the IEEE 802.11 or IEEE 802.15.4 protocols) for communications between the position tracking devices 16 and the host computer system 18.
  • the radio access points 30 may be in communication with the host 18 via a data transfer network 20 such as, for example, a LAN, a corporate intranet, a WAN, a MAN, a TCP/IP network, a broadband computer network, a wireless communication network, or a combination of one or more of these data transfer networks.
  • a data transfer network 20 such as, for example, a LAN, a corporate intranet, a WAN, a MAN, a TCP/IP network, a broadband computer network, a wireless communication network, or a combination of one or more of these data transfer networks.
  • the reference point transmitters 28 and the radio access points 30 may be strategically placed throughout the high-resolution area 14 so as to avoid interference caused by obstructions in the environment and/or co-channel interference, yet reduce the number of each that is needed to provide adequate position resolution and communications with the host 18. For example, in various applications it may be advantageous to position the reference point transmitters 28 points along or near common travel paths for the objects in the environment.
  • FIG. 2 is a block diagram of a tracking device 16 according to various embodiments of the present invention.
  • the tracking device 16 may compute its estimated position based on (1) inputs from a number of inertial sensors in an inertial sensor assembly 40 and (2) received signals from the reference position transmitters 28.
  • the inertial sensor assembly 40 may detect movement by the tracking device 16, such as lateral, vertical or rotational movement, and provide corresponding data signal inputs to a processor 42.
  • the inertial sensor assembly 40 may include a number of accelerometers (not shown) and/or gyroscopes (not shown) for detecting motion by the tracking device 16.
  • three accelerometers and three gyroscopes may be used, one for each or multiple degree(s) of freedom (x, y, z, roll, pitch, yaw) for the tracking device 16.
  • a lesser or greater number of accelerometers and/or gyroscopes may be used.
  • the accelerometers /gyroscopes may be, for example, micro- devices, such as MEMS-based devices.
  • different types of inertial sensors may be used, such as optical-based inertial sensors.
  • the processor 42 may include one or more microprocessors.
  • the tracking device 16 may employ parallel processing.
  • the tracking device 16 may include a reference position receiver 44, a number of RP transceivers 46A- C, and a wireless telephone network transceiver 48.
  • the reference position receiver 44 may receive signals from the reference point transmitters 28 and forward the received reference position information to the processor 42 to aid in the position determination process.
  • the RP transceiver 46A may communicate with the radio access points 30 and/or with other tracking devices 16. As such, the RF transceiver 46A may report object location information (as computed by the processor 42) back to the host 18 via the radio access points 30, as well as receive control and monitoring signals from the host 18 and send responses thereto.
  • the wireless telephone network transceiver 48 may communicate with a wireless telephone network that includes base stations 50 (see Figure 1). Information from such communications may be used by the processor 42, as described below, in calculating the location information of the object in the wide area mode of operation. While in the wide resolution area 12, the tracking device 16 may communicate with the host 18 via, for example, satellite radio signals or other long-range radio communication signals sent from the RF transceiver 46B and received by a transceiver 21 associated with the host 18. According to other embodiments, the tracking device 16 may communicate with the host via a telephone network (not shown), such as the wireless telephone network associated with the base stations 50. The tracking device 16 may also include a memory device 52 and a power source, such as battery 54.
  • the memory device 52 may be in communication with the processor 42, and store instructions and data for the processor 42.
  • the memory device 52 may be implemented, for example, as one or more RAM units or flash memory devices, or any other suitable memory device(s).
  • the battery 54 supplies power to the various power- consuming components of the tracking device 16.
  • the tracking device 16 may include a high-resolution module 60 and a wide area resolution module 62 for computing the position of the tracking device in the corresponding modes of operation.
  • the modules 60, 62 may be implemented as software code to be executed by the processor 42 using any suitable computer instruction type such as, for example, Java, C, C++, Visual Basic, etc., using, for example, conventional or object-oriented techniques.
  • the software code may be stored as a series of instructions or commands on a computer readable medium, such as a memory device 52.
  • a wireless signal transmitted from points of egress/ingress between the wide resolution areas 12 and the high-resolution areas 14, such as from a transmitter 66 at gate 68 in Figure 1, may be used by the tracking device 16 to switch between the wide area mode and the high-resolution mode. That is, when the tracking device 16 receives the egress/ingress activation signal (via, e.g., the RF transceiver 46C), the tracking device 16 may switch its mode of operation, for example, from the high resolution mode to the wide area mode, or vice versa, depending on whether the tracking device is leaving or entering the high resolution area 14.
  • a number of such transmitters 66 such as one for each point of egress/ingress, may be used.
  • the modes of the tracking device 16 maybe manually toggled, such as with a bistable switch at the point of egress/ingress.
  • the tracking device 16 may determine its general position, according to various embodiments, based on cell-ID information received from the wireless telephone network base stations 50. That is, the tracking device 16 may be in communication with one of the base stations 50 of the wireless telephone network according to conventional call hand-off technology employed by the wireless telephone network and obtain the Cell-ID from the base station 50 in the hand-shake/registration communications with the base station 50.
  • Each base station 50 may serve a certain geographic area (a "cell site").
  • the wide area resolution module 62 of the tracking device 16 may correlate the received Cell-ID information to map information stored in the memory device 52 to determine the general location of the tracking device 16 (e.g., within the geographic area covered by the base station 50). Thus, as the object travels between cell sites as it travels throughout the wide resolution area 12, the wide area resolution module 62 may update its position as it enters each new cell site based on the new Cell-ID information that it receives.
  • the geographic area of a cell in a wireless telephone network typically ranges from hundreds to a few thousand meters. In such a scheme, the positioning resolution varies as the object moves from areas with higher base station densities to areas with lower base station densities.
  • the wide area resolution module 62 determines the object is in the region based on the received cell-ID, it may further refine its location estimation to be on or near the highway in the geographic region covered by the relevant base station 50.
  • the pre-planned route information may be stored in the memory device 52 of the tracking device 16, or it may be stored in a memory unit associated with the host 18 (e.g., the database 24). In the later case, the host 18 may compute the refined location estimation based on the pre-planned route information.
  • the wide area resolution module 62 may reside with the host 18.
  • the cell-site map information may be stored in the database 24 and the tracking device 16 may report back to the host 18 the Cell-ID information. The host 18 may then perform the correlation between the Cell-ID information and the cell-site map information to compute the general location of the tracking device 16.
  • the tracking device 16 may include a GPS receiver (not shown) to aid in the location determination process.
  • the wide area resolution module 62 may use both inputs to verify the location of the object.
  • the high-resolution module 60 of the tracking device 16 may compute the location and orientation of the object based on the inertial sensor inputs and the inputs from the wireless aiding system.
  • the inertial sensors may provide outputs that measure motions of the object, such as linear accelerations and rates of rotation.
  • the vector a is used to identify the measured x, y and z accelerations
  • the vector w is used identify the x, y, and z rotation rates as measured by the inertial sensor assembly 40.
  • Figure 3 is a diagram of a state estimation algorithm employed by the high- resolution module 60 according to various embodiments of the present invention to estimate the state of the tracked object in a high resolution area.
  • three different frames of orientation are considered in describing the process: (1) the Inertial Frame, which is the coordinate frame of the tracking device 16, (2) the Body Frame, which is the coordinate frame of the object to which the tracking device 16 is affixed or connected (in both cases x is in the body forward direction), and (3) the Navigation Frame, which is the coordinate frame of the environment in which the object is moving.
  • the "state" of the object computed by the high-resolution module 60 may include values for the following parameters (where vectors are denoted in lower case with an " ⁇ " and matrices are denoted in upper case with an " ⁇ ”):
  • ⁇ the bias estimate, ⁇ , a vector representing the bias in ⁇ and w (denoted as b" and ⁇ respectively);
  • ⁇ the active mode, m, a scalar representing the current mode of the object (e.g., stopped, moving in x, y, and/or z, etc.);
  • the state estimate may comprise a subset of these parameters.
  • the current mode of the object may be a motion mode that is characterized by certain motion patterns or signatures indicative of the mode.
  • one mode may be "moving forward,” which may be characterized by a large acceleration in the x direction and lasting until a large deceleration.
  • Another mode may be "stopped with the ignition off,” which may be characterized by extremely small or no acceleration in the x, y or z direction, as well as extremely small or no rotation.
  • the mode “stopped with the ignition on” may be characterized by slightly greater acceleration or rotation than the "stopped with the ignition off mode, but still with relatively small acceleration and rotation measurements.
  • Other modes such as “turning,” “moving backward,” etc.
  • the current mode of the object may be detected by matching the current motion signatures to the patterns of the defined modes.
  • the current mode of the object may be used, as described below, in determining the location or state of an object because kinematic (or object movement) models may be constructed and used to define and/or limit the possible movements of the object when in a particular mode.
  • the current mode detector 82 may also reference the buffer S3 to recall when the last mode transition occurred.
  • the "state" estimate of the object may include values for the parameters P , b , I , R , m, v , and £ , or a subset of these parameters.
  • the correction inputs may be represented by the correction information matrix C , which may include several vectors, including P' v a u
  • mode transition correction information from the current state estimator algorithm 86 may be stored in the buffer S4.
  • the correction algorithm 92 may check to see whether any corrections have arrived in the buffer S4 and, if so, apply those corrections to the state estimates in the buffer S2 to generate corrected state estimates.
  • the corrector algorithm 92 may then compute and apply the corrections as it computes to the state estimates in the buffer S2 for the time period g s .
  • the state estimation at time t k-p-q, where q is an additional delay to account for the corrected information, may then be supplied as the output of the high resolution state estimation algorithm.
  • g s such that the corrector algorithm 92 can work on all past states.
  • the current mode state estimator 86 may use the new corrected state estimate as it computes the ongoing states estimates for the object.
  • a vector & of the correction history e.g., a list of the last / time points where a
  • a — L' /2 J 1 state correction was provided (e.g., U' * ""5 sJ) 5 may be stored in the buffer S3 at block 94.
  • the buffer S3 may also store a vector ⁇ of the mode history, e.g., a list of the lastj
  • the buffer S2 may store data at a slower rate than the other buffers.
  • the buffer S2 may store data at a rate of 1 Hz, whereas the other buffers may store data at a rate of 96 Hz. In that case, the buffer S2 stores every 96 th value.
  • its time stamp may indicate the necessary fractional time stamp adjustment.
  • the process of the detecting the current mode of the object may be a function of the various modes that the body (object) supports and the ease with which transitions between the modes can be detected. Typically, a conclusive decision that a mode transition detection is valid takes a period of time, p, to confirm the transition.
  • a generic process for detecting the current mode of the body/object according to various embodiments of the present invention is shown in Figure 4.
  • the state estimate for the straight integration for this time period may be stored in a buffer (buffer SS) at block 101.
  • the state estimate for the various motion models may be stored in buffers (buffers SMl to SMN) at blocks 104.
  • buffers SMl to SMN buffers SMl to SMN
  • a curve-fitting algorithm may be used to select the current mode.
  • a disadvantage of using a curve fitting algorithm is that to generate one time- increment of state estimation for each of the N motion models and the straight integration, (N+ 1) * p calculations must be performed, which may be too computationally expensive for some applications.
  • the current mode estimation can be performed at a lower frequency than the actual state estimation.
  • the resolution can be increased to better identify the transition time.
  • statistical analysis can also or alternatively be performed on the inertial sensor data to detect the current mode. For example, if the body is a car, which is either stationary or moving, statistical analysis of acceleration in the x direction may be sufficient to detect motion. For instance, the statistical analysis algorithm may analyze the standard deviation of a moving time window of the acceleration values. Changes in the standard deviation may be used to indicate mode transitions. The amount of time spent in the mode may then be used to ensure that the mode change detection was valid before a final decision is made that a mode transition has occurred.
  • Figure 5 is a diagram of the process of the current mode state estimator algorithm
  • the state estimate may be read from the buffer SS (see block 101, Figure 4).
  • a Kalman filter 114 may take the two different state estimates and corresponding confidence factors (based on, e.g., known sensor noise and known model shortcomings) to compute a state estimate that is a weighted sum of the two state estimates.
  • the Kalman filter 114 may be a standard Kalman filter or an adaptive one. According to various embodiments, a number of adaptive, cascaded Kalman filters may be used.
  • the parameters of the filter(s) may be derived from noise characteristics of the inertial sensors, the accuracy of the current mode motion model 112 and other tuning.
  • the state estimate corrector algorithm 92 may correct the state estimates stored in the buffer S2 based on the corrective information stored in the buffer S4.
  • the corrector algorithm 92 may differentiate between different types of corrective data in making corrections. For example, in various embodiments, the corrector algorithm 92 may differentiate between frequent and infrequent correction types. For infrequent corrections, such as when a position update is provided (such as from one of the reference position transmitters 28), the appropriate heading and/or velocity corrections that would shift the estimated position of the object to the updated position are computed. In making this determination, the initial heading information may be assumed to be incorrect and that the velocity error accumulated linearly. Once the heading and velocity corrections (and sometimes the bias corrections) are calculated, the results may be applied to correct the entire state trajectory in the buffer S2. In various embodiments, the corrector algorithm 92 may use a closed form solution to determine the heading and velocity corrections based on the estimated object location (without corrective inputs) and the updated object location.
  • Vj and %i denote the position, speed, and speed heading, respectively, at time i*dt, and
  • Jl be a unit heading vector in the navigation frame at time i.
  • Let ' be the rotation matrix that maps from the inertial frame to the navigation frame.
  • some correction information is given and its impact on the current state is to be calculated.
  • Three types of error may be considered: (1) velocity estimation errors due to accelerometer noise and incorrect initial conditions, (2) speed heading errors due to gyroscope noise and incorrect initial conditions, and (3) accumulating velocity error due to both.
  • velocity estimation errors (Case 1), the following types of velocity estimation errors should be accommodated while performing dead reckoning from the initial to the final position of an object:.
  • the Vo value may be wrong, and all v, need to be incremented by dv in
  • the estimate from vo to V n may be accumulating bias linearly, i.e., v, need to f be incremented by i*dv in some heading J ' .
  • the calculation from vo to V n may be accumulating bias with an arbitrary weight sequence and v, need to be incremented by w, * dv in some
  • - ⁇ is typically equal to l ' since the speed heading is typically in the body-x direction and there is minimal body-y or body-z speed to f correct.
  • each Jl is known and given at time i*dt. If one wants to accommodate error accumulation in all axes in the body frame, representing the three sensor biases, then
  • the correction information may be a new velocity (i.e. dv and * ) and the new position may be calculated.
  • F Ff error accrual it may be represented by a series of varying ' .
  • the new point may be given as:
  • This equation can then be used at time n to accommodate the correction information obtained.
  • the last equation above applies to the case for a vehicle where the initial heading assumption was wrong and velocity error is accumulating (Case 3 above). In this case, if a position update is provided and given a new point P° , this correction can be
  • Pr in the direction * l " leads to Pc .
  • the amount of translation to Pc is adjusted by proper selection of the dv value. Alternatively, one could first translate P « to a point P'
  • Figures 6 and 7 provide a simplified example of how the reference position transmitters 28 may be used to correct/update the position of the object in the high- resolution mode.
  • Figure 6 is a simplified diagram of a high-resolution area 14 with walls/obstacles 150 situated throughout the environment.
  • Figure 7 shows the x- and y- position error in the calculated position of the object/tracking device 16 as a function of time as it moves throughout the environment.
  • the position of the object/tracking device 16 is updated/corrected such that the x and y errors are zero at time tl.
  • the host processing system 18 may have knowledge (stored in the database 24, for example) about physical constraints of the environment and make additional position refinements based on that information. For example, the host processing system 18 may know the location of certain walls or other permanently located obstacles in the environment and, based thereon, refine the reported position of an object if the reported position coincides with such a wall or obstacle. Also, for certain object types, the host processing system 18 may assume that no two objects are in the same position at the same time.
  • FIG 8 is a diagram of the tracking device 16 according to another embodiment of the present invention.
  • the tracking device 16 additionally includes a power management module 160.
  • the power management module 160 may be implemented as software code to be executed by the processor 42 using any suitable computer instruction type such as, for example, Java, C, C++, Visual Basic, etc., using, for example, conventional or object-oriented techniques.
  • the software code may be stored as a series of instructions or commands on a computer readable medium, such as a memory device 52.
  • the power management module 160 may receive the inputs from the inertial sensor assembly 40 and, based thereon, dete ⁇ nine an appropriate power level for the tracking device 16 (such as, e.g., full power, reduced duty cycle, hibernation or sleep mode) that is needed for proper operation of the tracking device 16 at that particular moment.
  • an appropriate power level for the tracking device 16 such as, e.g., full power, reduced duty cycle, hibernation or sleep mode
  • the power management module 160 can, for example, cause the processor 42 to enter a sleep mode if no (or minimal) movement is detected for a certain time period.
  • the power management module 160 may select a reduced duty cycle mode when the tracking device 16 is in the wide area resolution mode and select a full power mode when the tracking device 16 is in the high resolution mode (except when the processor 42 enters the sleep mode due to lack of movement, for example, regardless of operational mode).
  • this description of the power management module 160 is in the context of a tracking device with an on-board processor, such a power management module that is responsive to inertial sensor inputs in selecting the power level can be used for any device with an on-board processor.
  • the position-tracking device 16 could be mounted on, attached to, or otherwise carried by a mobile vehicle and used to determine the position of objects located throughout an environment as the mobile vehicle moves throughout the environment.
  • Figure 9 illustrates a system 170 according to such an embodiment for determining the location of an object 172.
  • the system 170 may be utilized to track the respective locations of any number of objects 172, although only one such object is shown in Figure 9 for purposes of simplicity.
  • the system 170 includes an object location tracker 174 and a computer system 176 in wireless communication with the object location tracker 174.
  • the object location tracker 174 is for attachment to a vehicle 178 and comprises an object identification reading device 180 and the position-tracking device 16.
  • the vehicle 178 may be any type of vehicle capable of movement.
  • the vehicle 178 may be a pushcart such as a book cart or a shopping cart.
  • the vehicle 178 may be a motorized vehicle such as a car, a truck, a forklift, etc. According to other embodiments, the vehicle 178 may be an autonomous robot. According to yet other embodiments, the mobile vehicle may be a person who is walking around the environment. Although only one object location tracker 174 is shown in Figure 9, the system 170 may utilize a plurality of object location trackers 174, with each respective object location tracker 174 attached to a different vehicle 178.
  • the object identification reading device 180 is for sensing object identification indicia 173 on the object 172.
  • the object identification indicia 173 may be embodied, for example, in the form of a radio frequency identification (RF ID) tag on the object 172, a bar code on the object 172, a character such as a letter, a numeral, a symbol, etc. on the object 172, or any combination thereof on the object 172.
  • the object identification reading device 180 may include, for example, a radio frequency identification reader for sensing a RF ID tag on the object 172, a bar code scanner for reading a bar code on the object 172, a camera with optical character recognition (OCR) for recognizing characters on the object 172, etc. or any combination thereof.
  • OCR optical character recognition
  • the vehicle 178 may carry multiple reading devices with different coverage areas.
  • the device 174 may have a reading device 180 for each shelf height.
  • the device 174 may include a rod with an RFID reader antenna sticking out for each shelf height.
  • the device 174 may include different types of reading devices 180, such as a barcode scanner and an RFID reader, etc.
  • the identification indicia read from those fixed-position objects by the reading device(s) 180 can be used to aid in the location determination process much like a reference position signal received from one of the reference position signal transmitters 28.
  • the position tracking device 16 can use that information to aid in the location determination process.
  • the position-tracking device 16 may be as described above.
  • the position-tracking device 16 may include an inertial sensor assembly 40, a processor 42, a reference position receiver 44, a number of RF transceivers46A-C, a wireless telephone network transceiver 48, a memory device 52 and a power source 54.
  • the position-tracking device 16 may also include a high resolution module for computing the location of the object location tracker 174 (and hence the mobile vehicle to which the tracker 174 is attached) when the system 170 is in a high resolution operation mode, and a wide area resolution module for computing the location of the object location tracker 174 when the system 170 is in a wide area resolution mode.
  • the position-tracking device 16 may utilize GPS receiver for tracking it location.
  • the position- tracking device 16 may use a combination of a GPS receiver and the inertial sensor technique described in more detail above.
  • the position tracking device 16 may interpolate between reference points in determining its position. As described above, a time trajectory between the two reference positions may be computed by the high resolution module 60 (see Figure 2) based on the detected motion modes of the mobile vehicle, Kalman filtering, etc. That way, the location of the tracking device 16 between the reference points where the identification indicia of the object was read may be determined.
  • the computer system 176 is in communication with the object location tracker 174 and may be similar to the host computer 18 described hereinabove.
  • the sensed object identification indicia and the updated location information of the object location tracker 174 are transmitted wirelessly to the computer system 176.
  • the facility does not need to provide ubiquitous wireless communication coverage. Wireless coverage in a small area may be enough so long as the vehicle 178 passes through this coverage area at satisfactory intervals.
  • the computer system 176 may include a correlation module 184 for associating the sensed object identification indicia 173 of the object 172, as determined by the reading device 180, with a location in the environment based on the position of the object location tracker 174 in the environment, as determined by the position-tracking device 16, when the object identification reading device 180 senses the object identification indicia 173.
  • the correlation module 180 may update and filter the received object location information to obtain near real-time object location information for the objects in the environment.
  • the correlation module 180 can use the redundant location information from the multiple trackers 174 to refine the location of the objects.
  • the object location information may be stored in the database 54 and/or used by other logistics systems, as described above.
  • the computer system 176 may also include an imaging module 186 for generating a representation of the environment and the locations of each tracked object 172 in the environment.
  • the representation may be, for example, printed, or displayed on a monitor to show the location of each tracked object 172 in an environment.
  • the correlation module 184 and the imaging module 184 may be implemented as software code to be executed by the computer system 176 using any suitable computer instruction type.
  • the software code may be stored as a series of instructions or commands on a computer readable medium.
  • a system 170 as described above may be used, for example, to track the location of and identify inventory in the environment.
  • the object-tracking device 170 could be attached to a book return pushcart for use in a library to track the location of books in the library that have, for example, RF ID tags or bar codes that can be sensed by the reading device 180.
  • the object-tracking device 170 could be attached to shopping cart for use in a retail store (such as a grocery store) to track the location of inventory in the store.
  • the object-tracking device 170 could be attached to a forklift or other type of industrial vehicle for use in a warehouse or transportation yard to track the location of inventory or other goods.
  • the object-tracking device 170 could be attached to vehicle that roams around a parking lot to track the location of cars or other vehicles in the parking lot that have, for example, RF ID tags or bar codes that can be sensed by the reading device 180.

Abstract

L'invention concerne un système de poursuite de position permettant de poursuivre la position d'un objet. Dans divers modes de réalisation, ce système de poursuite comprend un dispositif de poursuite connecté ou fixé à l'objet à poursuivre. Ce dispositif de poursuite peut comprendre, entre autres, un ensemble capteurs inertiels, des émetteurs-récepteurs radio et un processeur. Le système de poursuite de position peut également comprendre un système de traitement hôte en communication avec le dispositif de poursuite. Le système de poursuite de position peut fournir des informations de position à résolution variable basées sur l'environnement dans lequel l'objet se déplace. Dans une zone 'résolution large', le système peut calculer une position générale pour l'objet en fonction d'une architecture de corrélation carte/identification de cellule de réseau téléphonique sans fil. Dans une zone haute résolution, une résolution de position supérieure peut être obtenue à partir de la combinaison d'un système d'aide sans fil et d'entrées provenant des capteurs inertiels. En mode haute résolution, le système peut exploiter différents schémas de mouvement pouvant être identifiés comme 'signatures' de mouvement caractéristiques de certains types de mouvement. Des modèles cinématiques (ou de mouvement d'objet) peuvent être construits en fonction de ces signatures de mouvement, et le système de poursuite de position peut estimer l'état de l'objet en fonction du modèle cinématique pour le mode courant de l'objet. Un filtrage Kalman en cascade et adaptatif peut être utilisé dans l'analyse pour estimer plus précisément la position et la vitesse de l'objet en fonction du schéma de mouvement identifié.
PCT/US2006/004313 2005-02-10 2006-02-08 Systeme de poursuite de position WO2006086398A2 (fr)

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US11/054,905 2005-02-10
US11/054,881 US7236091B2 (en) 2005-02-10 2005-02-10 Position-tracking system
US11/054,905 US7245215B2 (en) 2005-02-10 2005-02-10 Position-tracking device for position-tracking system
US11/054,881 2005-02-10
US11/175,081 2005-07-05
US11/175,081 US7321305B2 (en) 2005-07-05 2005-07-05 Systems and methods for determining a location of an object

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CN101949953A (zh) * 2010-07-30 2011-01-19 中国科学院软件研究所 基于三维加速度无线传感器网络的货物状态监测方法
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CN105158732A (zh) * 2015-06-24 2015-12-16 浙江工业大学 一种无线传感器网络协助的移动机器人自定位方法
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CN108182799A (zh) * 2018-01-09 2018-06-19 吉旗（成都）科技有限公司 一种高速偏离监控的方法
CN109153124A (zh) * 2016-06-20 2019-01-04 X开发有限责任公司 移动系统的本地化
CN109917441A (zh) * 2019-04-02 2019-06-21 河北工业大学 一种基于窄带物联网的运动物体姿态定位装置及方法
CN110381446A (zh) * 2019-07-10 2019-10-25 宁夏仲检检测有限公司 一种抽样人员运动轨迹追踪方法
CN110715661A (zh) * 2018-07-13 2020-01-21 索尼移动通讯有限公司 在运输系统中跟踪物体的方法、设备和计算机程序产品
CN110832546A (zh) * 2017-07-07 2020-02-21 三星电子株式会社 用于设备追踪的系统和方法
WO2020188176A1 (fr) * 2019-03-21 2020-09-24 Psa Automobiles Sa Procédé et dispositif de détermination de l'activité d'au moins un véhicule se déplaçant à l'intérieur d'une zone couverte

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CN109153124A (zh) * 2016-06-20 2019-01-04 X开发有限责任公司 移动系统的本地化
CN109153124B (zh) * 2016-06-20 2021-10-01 X开发有限责任公司 移动系统的本地化
CN110832546B (zh) * 2017-07-07 2024-03-08 三星电子株式会社 用于设备追踪的系统和方法
CN110832546A (zh) * 2017-07-07 2020-02-21 三星电子株式会社 用于设备追踪的系统和方法
CN108182799A (zh) * 2018-01-09 2018-06-19 吉旗（成都）科技有限公司 一种高速偏离监控的方法
CN110715661A (zh) * 2018-07-13 2020-01-21 索尼移动通讯有限公司 在运输系统中跟踪物体的方法、设备和计算机程序产品
CN110715661B (zh) * 2018-07-13 2023-09-29 索尼网络通信欧洲公司 在运输系统中跟踪物体的方法、设备、系统和存储介质
WO2020188176A1 (fr) * 2019-03-21 2020-09-24 Psa Automobiles Sa Procédé et dispositif de détermination de l'activité d'au moins un véhicule se déplaçant à l'intérieur d'une zone couverte
FR3094096A1 (fr) * 2019-03-21 2020-09-25 Psa Automobiles Sa Procédé et dispositif de détermination de l’activité d’au moins un véhicule se déplaçant à l’intérieur d’une zone couverte
CN109917441A (zh) * 2019-04-02 2019-06-21 河北工业大学 一种基于窄带物联网的运动物体姿态定位装置及方法
CN110381446A (zh) * 2019-07-10 2019-10-25 宁夏仲检检测有限公司 一种抽样人员运动轨迹追踪方法

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