US7015831B2
Expired / Lapsed
US
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Systems and methods for incrementally updating a pose of a mobile device calculated by visual simultaneous localization and mapping techniques
Assignee: FUTURE VISION HOLDINGS Inc
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Filing: 2003-12-17
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Granted: 2006-03-21
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Expires: 2023-12-17
Abstract
Abstract The invention is related to methods and apparatus that use a visual sensor and dead reckoning sensors to process Simultaneous Localization and Mapping (SLAM). These techniques can be used in robot navigation. Advantageously, such visual techniques can be used to autonomously generate and update a map. Unlike with laser rangefinders, the visual techniques are economically practical in a wide range of applications and can be used in relatively dynamic environments, such as environments in which people move. One embodiment further advantageously uses multiple particles to maintain multiple hypotheses with respect to localization and mapping. Further advantageously, one embodiment maintains the particles in a relatively computationally-efficient manner, thereby permitting the SLAM processes to be performed in software using relatively inexpensive microprocessor-based computer system.
Inventors
- 👤 L. Niklas Karlsson
- 👤 Paolo Pirjanian
- 👤 Luis Filipe Domingues Goncalves
- 👤 Enrico Di Bernardo
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-24 16:20
CPC Classifications
G; G05; G05D; G05D1/00; G05D1/02; G05D1/021; G05D1/0231; G05D1/0246; G01; G01C; G01C21/00; G01C21/10; G01C21/12; G01C21/20; G01C21/206; G05D1/0234; G05D1/0238; G05D1/024; G05D1/0242; G05D1/0248; G05D1/0268; G05D1/0272; G05D1/0274; G05D1/0276; G05D1/0278; G06; G06T; G06T7/00; G06T7/50; G06T7/55; G06T7/70; G06T7/73; G06T7/74; G06T2207/00; G06T2207/30; G06T2207/30204; Y; Y10; Y10S; Y10S901/00; Y10S901/01; Y10S901/46; Y10S901/47; Y10S901/50
Claims Analysis
Total Claims: 32
Claim 1
Independent Claim
143 words
A method of updating a map for autonomous localization and mapping for a device, the method comprising: receiving an indication that a landmark has been observed, where the landmark is associated with a landmark pose, and where the map comprises one or more landmarks; predicting a first device pose based on a change in pose from a prior update to device pose, wherein the change in pose is computed at least partly from dead reckoning data; predicting a second device pose based on a visual measurement relative to the observed landmark and based on a stored estimate of landmark pose; predicting a new pose for the device based on at least one of the first device pose and the second device pose; and using a statistical filter to update the corresponding landmark pose estimate based at least partly on the new device pose.
Claim 2
Independent Claim
143 words
A method of updating a map for autonomous localization and mapping for a device, the method comprising: receiving an indication that a landmark has been observed, where the landmark is associated with a landmark pose, and where the map comprises one or more landmarks; predicting a first device pose based on a change in pose from a prior update to device pose, wherein the change in pose is computed at least partly from dead reckoning data; predicting a second device pose based on a visual measurement relative to the observed landmark and based on a stored estimate of landmark pose; predicting a new pose for the device based on at least one of the first device pose and the second device pose; and using a statistical filter to update the corresponding landmark pose estimate based at least partly on the new device pose.
Claim 3
Dependent Claim
29 words
The method as defined in claim 1 , wherein the device corresponding landmark pose estimate robot, the method further comprising using the map for navigation in the mobile robot.
Claim 4
Dependent Claim
23 words
The method as defined in claim 1 , wherein predicting a second device pose further comprises using a model of visual measurement uncertainty.
Claim 5
Dependent Claim
26 words
The method as defined in claim 1 , wherein predicting a first device pose further comprises using a model of uncertainty in a dead reckoning measurement.
Claim 6
Dependent Claim
17 words
The method as defined in claim 1 , wherein the statistical filter corresponds to a Kalman filter.
Claim 7
Dependent Claim
22 words
The method as defined in claim 1 , wherein the visual measurement is derived from a single camera as a visual sensor.
Claim 8
Dependent Claim
16 words
The method as defined in claim 1 , wherein the method is performed in real time.
Claim 9
Dependent Claim
26 words
The method as defined in claim 1 , wherein predicting the new pose for the device is performed without iterative estimations of device poses between measurements.
Claim 10
Dependent Claim
22 words
The method as defined in claim 1 , wherein updating the map is performed without iterative estimations of device poses between measurements.
Claim 11
Dependent Claim
27 words
The method as defined in claim 1 , further comprising maintaining multiple hypotheses as multiple particles, where a particle includes a map and a device pose estimate.
Claim 12
Dependent Claim
157 words
A circuit for updating a map for autonomous localization and mapping for a device, the circuit comprising: a circuit configured to receive an indication that a landmark has been observed, where the landmark is associated with a landmark pose, and where the map comprises one or more landmarks; a circuit configured to predict a first device pose based on a change in pose from a prior update to device pose, wherein the change in pose is computed at least partly from dead reckoning data; a circuit configured to predict a second device pose based on a visual measurement relative to the observed landmark and based on a stored estimate of landmark pose; a circuit configured to predict a new pose for the device based on at least one of the first device pose and the second device pose; and statistical filter that updates the corresponding landmark pose estimate based at least partly on the new device pose.
Claim 13
Dependent Claim
157 words
A circuit for updating a map for autonomous localization and mapping for a device, the circuit comprising: a circuit configured to receive an indication that a landmark has been observed, where the landmark is associated with a landmark pose, and where the map comprises one or more landmarks; a circuit configured to predict a first device pose based on a change in pose from a prior update to device pose, wherein the change in pose is computed at least partly from dead reckoning data; a circuit configured to predict a second device pose based on a visual measurement relative to the observed landmark and based on a stored estimate of landmark pose; a circuit configured to predict a new pose for the device based on at least one of the first device pose and the second device pose; and statistical filter that updates the corresponding landmark pose estimate based at least partly on the new device pose.
Claim 14
Dependent Claim
31 words
The circuit as defined in claim 11 , wherein the device corresponds to a mobile robot, where the circuit is embodied in the mobile robot for navigation of the mobile robot.
Claim 15
Dependent Claim
26 words
The method as defined in claim 11 , wherein the circuit configured to predict a second device pose is further configured to model visual measurement uncertainty.
Claim 16
Dependent Claim
29 words
The method as defined in claim 11 , wherein the circuit configured to predict a first device pose is further configured to model uncertainty in a dead reckoning measurement.
Claim 17
Dependent Claim
180 words
A computer program embodied in a tangible medium for updating a map for autonomous localization and mapping for a device, the computer program comprising: a module with instructions configured to receive an indication that a landmark has been observed, where the landmark is associated with a landmark pose, and where the map comprises one or more landmarks; a module with instructions configured to predict a first device pose based on a change in pose from a prior update to device pose, wherein the change in pose is computed at least partly from dead reckoning data; a module with instructions configured to predict a second device pose based on a visual measurement relative to the observed landmark and based on a stored estimate of landmark pose; a module with instructions configured to predict a new pose for the device based on at least one of the first device pose and the second device pose; and a module with instructions configured to use a statistical filter to update the corresponding landmark pose estimate based at least partly on the new device pose.
Claim 18
Dependent Claim
180 words
A computer program embodied in a tangible medium for updating a map for autonomous localization and mapping for a device, the computer program comprising: a module with instructions configured to receive an indication that a landmark has been observed, where the landmark is associated with a landmark pose, and where the map comprises one or more landmarks; a module with instructions configured to predict a first device pose based on a change in pose from a prior update to device pose, wherein the change in pose is computed at least partly from dead reckoning data; a module with instructions configured to predict a second device pose based on a visual measurement relative to the observed landmark and based on a stored estimate of landmark pose; a module with instructions configured to predict a new pose for the device based on at least one of the first device pose and the second device pose; and a module with instructions configured to use a statistical filter to update the corresponding landmark pose estimate based at least partly on the new device pose.
Claim 19
Dependent Claim
29 words
The computer program as defined in claim 15 , wherein the device corresponds to a mobile robot, wherein the computer program is used by the mobile robot for navigation.
Claim 20
Dependent Claim
33 words
The computer program as defined in claim 15 , wherein, the module with instructions configured to predict a second device pose further comprises instructions configured to use a model of visual measurement uncertainty.
Claim 21
Dependent Claim
36 words
The computer program as defined in claim 15 , wherein the module with instructions configured to predict a first device pose further comprises instructions configured to use a model of uncertainty in a dead reckoning measurement.
Claim 22
Dependent Claim
155 words
A circuit for updating a map for autonomous localization and mapping for a device, the circuit comprising: a means for receiving an indication that a landmark has been observed, where the landmark is associated with a landmark pose, and where the map comprises one or more landmarks; a means for predicting a first device pose based on a change in pose from a prior update to device pose, wherein the change in pose is computed at least partly from dead reckoning data; a means for predicting a second device pose based on a visual measurement relative to the observed landmark and based on a stored estimate of landmark pose; a means for predicting a new pose for the device based on at least one of the first device pose and the second device pose; and a statistical filter configured to update the corresponding landmark pose estimate based at least partly on the new device pose.
Claim 23
Dependent Claim
155 words
A circuit for updating a map for autonomous localization and mapping for a device, the circuit comprising: a means for receiving an indication that a landmark has been observed, where the landmark is associated with a landmark pose, and where the map comprises one or more landmarks; a means for predicting a first device pose based on a change in pose from a prior update to device pose, wherein the change in pose is computed at least partly from dead reckoning data; a means for predicting a second device pose based on a visual measurement relative to the observed landmark and based on a stored estimate of landmark pose; a means for predicting a new pose for the device based on at least one of the first device pose and the second device pose; and a statistical filter configured to update the corresponding landmark pose estimate based at least partly on the new device pose.
Claim 24
Dependent Claim
28 words
The circuit as defined in claim 19 , wherein the device corresponds to a mobile robot, and where the circuit is embodied in the mobile robot for navigation.
Claim 25
Independent Claim
226 words
A method of automatically updating a map for navigation with a Kalman filter, the method comprising: providing the map, where the map comprises one or more landmarks, where a landmark includes a landmark pose estimate and an uncertainty measure, where a landmark pose estimate is initially based on a device pose estimate in a global reference frame corresponding to when the landmark was added to the map, and where the landmark pose estimate is updated as the landmark is re-encountered; predicting a landmark pose based at least in part on a reference device pose and one or more measurements of relative pose between the device pose and the landmark, wherein the one or more measurements of relative device pose are based at least in part on one or more visual measurements; computing the uncertainty measure for error in the predicted landmark pose; using the Kalman filter, wherein: inputs to the Kalman filter comprise the predicted landmark pose, the uncertainty measure thereof, a previous estimate of landmark pose, and the uncertainty measure thereof; and outputs of the Kalman filter comprise an updated estimate of landmark pose and the uncertainty measure thereof; and storing the updated landmark pose estimate and the updated uncertainty measure in the map such that the updated landmark pose estimate and the updated uncertainty measure can be updated again when the landmark is re-encountered.
Claim 26
Independent Claim
226 words
A method of automatically updating a map for navigation with a Kalman filter, the method comprising: providing the map, where the map comprises one or more landmarks, where a landmark includes a landmark pose estimate and an uncertainty measure, where a landmark pose estimate is initially based on a device pose estimate in a global reference frame corresponding to when the landmark was added to the map, and where the landmark pose estimate is updated as the landmark is re-encountered; predicting a landmark pose based at least in part on a reference device pose and one or more measurements of relative pose between the device pose and the landmark, wherein the one or more measurements of relative device pose are based at least in part on one or more visual measurements; computing the uncertainty measure for error in the predicted landmark pose; using the Kalman filter, wherein: inputs to the Kalman filter comprise the predicted landmark pose, the uncertainty measure thereof, a previous estimate of landmark pose, and the uncertainty measure thereof; and outputs of the Kalman filter comprise an updated estimate of landmark pose and the uncertainty measure thereof; and storing the updated landmark pose estimate and the updated uncertainty measure in the map such that the updated landmark pose estimate and the updated uncertainty measure can be updated again when the landmark is re-encountered.
Claim 27
Dependent Claim
16 words
The method as defined in claim 21 , further comprising using the map for robot navigation.
Claim 28
Dependent Claim
29 words
The method as defined in claim 21 , wherein computing the uncertainty measure further comprises computing uncertainty in a visual measurement and computing uncertainty in a dead reckoning measurement.
Claim 29
Dependent Claim
32 words
The method as defined in claim 21 , wherein the reference device pose corresponds to a device pose corresponding to a prior update of the device pose in the global reference frame.
Claim 30
Dependent Claim
18 words
The method as defined in claim 21 , where the prior update corresponds to the most recent update.
Claim 31
Dependent Claim
99 words
The method as defined in claim 21 , wherein the measured landmark pose equals: L ^ m k = [ s m ( 2 ) + Δ 1 vis cos ( s m ( 4 ) + Δ 2 vis ) s m ( 3 ) + Δ 1 vis sin ( s m ( 4 ) + Δ 2 vis ) [ ( s m ( 4 ) + Δ 3 vis + π ) mod 2 π ] - π ] .
Claim 32
Dependent Claim
27 words
The method as defined in claim 21 , further comprising maintaining multiple hypotheses as multiple particles, where a particle includes a map and a device pose estimate.
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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) | 2009-03-20 | 2009-09-19 | 2010-03-21 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2013-03-20 | 2013-09-19 | 2014-03-21 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2017-03-20 | 2017-09-19 | 2018-03-21 | $7700.00 | Window Closed / Lapsed |