Patent US6323807B1 successfully refreshed from Google Patents.
US6323807B1
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Indoor navigation with wearable passive sensors
Assignee: Mitsubishi Electric Research Laboratories Inc
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Filing: 2000-02-17
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Granted: 2001-11-27
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Expires: 2020-02-17
Abstract
Abstract A wearable device is configured for navigating in an indoor environment. The device includes passive sensors for measuring environmental physical conditions at known locations in the indoor environment and at an unknown locations in the indoor environment. A wearable computer is coupled to passive sensors. The computer is configured to construct a first statistical model of the environment according to the measured physical conditions at the known locations and a second statistical model of the environment according to the measured physical conditions at the unknown locations. Processing means of the computer determines a probability that the unknown locations correspond to the known locations by comparing the second statistical model to the first statistical model.
Inventors
- 👤 Andrew R. Golding
- 👤 Neal B. Lesh
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-07 19:12
CPC Classifications
G; G01; G01C; G01C21/00; G01C21/20; G01C21/206; G01S; G01S5/00; G01S5/02; G01S2205/00; G01S2205/01; G01S2205/02
Claims Analysis
Total Claims: 13
Claim 1
Independent Claim
107 words
A method for navigating in an indoor environment using a weareable computer device having a plurality of sensors, comprising the steps of: measuring a plurality of environmental physical conditions with passive sensors at a plurality of known locations in the environment; constructing a first statistical model of the environment according to the measured physical conditions; measuring the plurality of environmental physical conditions at unknown locations in the environment; constructing a second statistical model of the environment according to the measured physical conditions; determining a probability that the unknown location corresponds to any of the known locations by comparing the second statistical model to the first statistical model.
Claim 2
Independent Claim
107 words
A method for navigating in an indoor environment using a weareable computer device having a plurality of sensors, comprising the steps of: measuring a plurality of environmental physical conditions with passive sensors at a plurality of known locations in the environment; constructing a first statistical model of the environment according to the measured physical conditions; measuring the plurality of environmental physical conditions at unknown locations in the environment; constructing a second statistical model of the environment according to the measured physical conditions; determining a probability that the unknown location corresponds to any of the known locations by comparing the second statistical model to the first statistical model.
Claim 3
Dependent Claim
23 words
The method of claim 1 wherein the plurality of passive sensors include an accelerometer, a magnetometer, a light detector, and a temperature sensor.
Claim 4
Dependent Claim
19 words
The method of claim 1 wherein the statistical model represents the measured physical conditions as Gaussian probability distribution functions.
Claim 5
Dependent Claim
23 words
The method of claim 1 wherein navigation is performed by determining a probability of transitioning between the locations according to the statistical model.
Claim 6
Dependent Claim
119 words
The method of claim 1 wherein the measured physical conditions at each location l are given as readings are S={s l , . . . , s n }, and a posterior probability that the unknown location is the known location l is estimated using Baye's rule with a conditional independence assumption: P ( l | 〈 s 1 , … , s n 〉 ) = ( ∏ 1 ≤ i ≤ n P ( s i | l ) ) P ( l ) P ( 〈 s 1 , … , s n 〉 ) where P(s i |l) terms are determined from the first statistical model.
Claim 7
Dependent Claim
19 words
The method of claim 4 wherein the probability of transitioning between locations uses dead-reckoning information obtained from an accelerometer.
Claim 8
Dependent Claim
19 words
The method of claim 1 further comprising the step of: extracting, high level features from the measured physical conditions.
Claim 9
Dependent Claim
13 words
The method of claim 1 wherein the plurality of passive sensors are non-directional.
Claim 10
Dependent Claim
21 words
The method of claim 1 wherein the environment includes radio frequency transponders, and wherein the passive sensors include a radio receiver.
Claim 11
Dependent Claim
21 words
The method of claim 1 wherein the first and second statistical models only consider measured physical conditions within a predetermined range.
Claim 12
Independent Claim
120 words
An apparatus for navigating in an indoor environment, comprising: a plurality of passive sensors for measuring a plurality of environmental physical conditions at a plurality of known locations in the indoor environment, and at an unknown location in the indoor environment; a wearable computer device coupled to the plurality of passive sensors configured to construct a first statistical model of the environment according to the measured physical conditions at the plurality of known locations and a second statistical model of the environment according to the measured physical conditions at the unknown locations; and means for determining a probability that the unknown location corresponds to one of the known locations by comparing the second statistical model to the first statistical model.
Claim 13
Independent Claim
120 words
An apparatus for navigating in an indoor environment, comprising: a plurality of passive sensors for measuring a plurality of environmental physical conditions at a plurality of known locations in the indoor environment, and at an unknown location in the indoor environment; a wearable computer device coupled to the plurality of passive sensors configured to construct a first statistical model of the environment according to the measured physical conditions at the plurality of known locations and a second statistical model of the environment according to the measured physical conditions at the unknown locations; and means for determining a probability that the unknown location corresponds to one of the known locations by comparing the second statistical model to the first statistical model.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2004-11-26 | 2005-05-28 | 2005-11-27 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2008-11-26 | 2009-05-28 | 2009-11-27 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2012-11-26 | 2013-05-28 | 2013-11-27 | $7700.00 | Window Closed / Lapsed |