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APT: Accurate Outdoor Pedestrian Tracking with Smartphones. TsungYun 20130401. Outline. Introduction Preliminary E xperiment System and Mechanism Evaluation Conclusion. Introduction. Motivation - PowerPoint PPT Presentation
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APT: Accurate Outdoor Pedestrian Tracking with Smartphones
TsungYun 20130401
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Outline
• Introduction• Preliminary Experiment• System and Mechanism • Evaluation• Conclusion
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Introduction
• Motivation – Want to build a system to assist the blind people
with smartphones by providing accurate location information
– GPS measurements show error up to 15 meters in a clear-sky-view environment
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Introduction
• Observations– Pedestrians have regular movements patterns– Although GPS is unsatisfactory, it works well in
distinguishing between distant routes– Can easily generate augmented maps on a
smartphone• Dead-Reckoning algorithm • Map-Matching algorithm
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Introduction
• Dead-Reckoning algorithm – Accelerometer: walking step – Gyroscope: walking direction• Consume much less energy than GPS
• Map-Matching algorithm– Match a walking trace to a route on the map
• Challenges– Placement of the smartphone– Error-tolerant
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Preliminary Experiment
• Limitation of GPS system– GPS system achieved error up to 15 meter– GPS readings cannot be improved by itself solely
• First issue– If the GPS coordinate stabilizes, then it will not
change for at least several hours– staying in one place longer does not help improve
GPS accuracy
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Preliminary Experiment
• Collect 15-20 GPS coordinates at three locations at seven different days– Clear view of the sky
– Do not mention how far between these locations
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Preliminary Experiment
• Results show that– GPS readings at the
same location can differ up to 15 meters
– hard to find any obvious temporal or spatial correlation
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Preliminary Experiment
• Walks along a route 5 times– a large portion of this
route is covered by trees• Result shows– the error can still be
more than 20 meters– no obvious error pattern
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Preliminary Experiment
• Conclusion– We find that it is unlikely to improve localization
accuracy based solely on GPS
• In this work, the use of GPS is limited to help reduce route ambiguity in the Map-Matching algorithm
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Mechanism
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Mechanism I
• Dead-Reckoning – estimating distances– taking the double integral of acceleration results
in large error– a common approach is to count the number of
walking steps and then multiply it by the stride length• By finding the recurring patterns of accelerometer
readings
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Mechanism I
• Different placement of the phone has a large impact on the accuracy of each step counter– 6 recurring patterns– 3 recurring patterns
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Mechanism I
• No matter how the phone is placed, we find that acceleration always shows some recurring patterns– define an up-down pattern as a step– A pattern ‘10’ or ‘1 0’ is defined as a step∧
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Mechanism I
• Using acceleration magnitude, instead of acceleration in a certain direction, can tolerate different ways pedestrians carry the phone
• Step length can be measured or trained in advance
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Mechanism I
• Dead-Reckoning – estimating direction– two Cartesian frame of reference– xyz axes V.S. XYZ axes– We can obtain • x y z data
– We need • Z data
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Mechanism I
• straight line -> 90° left turn -> straight line– angular displacement around any axis remains
roughly the same before/after the turn
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Mechanism I
• straight line -> 90° left turn -> straight line– acceleration does not fluctuate much before/after
the turn, but is quite unusual during the turn
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Mechanism I
• angular displacement around Z-axis
– α, β, γ are the angular displacements around x, y, z axis– µx , µy , µz are the acceleration readings in x, y, z
direction
– the average acceleration during a straight walk should approximate gravity
– Z-axis vector (the gravity) is decomposed into three components ???????
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Mechanism I
• The angular displacement is 91.56◦ in this case– But the error (1.56◦) is inevitable
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Mechanism II
• Map-Matching algorithm
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Mechanism II
• Map-Matching algorithm
Use GPS here trial-and-error
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Mechanism II
• Map-Matching algorithm
– Two position fixes can determine a matching– Basic idea : Trial-and-error• Starting from one position fix, find out all possible
routes• use subsequent points in the walk to test and extend
these routes
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Mechanism II
• Map-Matching algorithm– Assume “perfect information”• First assume that accelerometer, gyroscope, GPS
readings are 100% accurate– Update when • New step• New turn • New GPS reading
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Mechanism II
Use GPS here
Reversely check
↑ Use GPS here if multiple routes to reduce ambiguity
↑ Use GPS here
Use MAP here
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Mechanism II
• Dealing with errors– Initial routes• We enumerate all possible locations of the user on the
map by considering GPS error– A new step• An adjacent route segment is possible if walking to it
only requires a shallow turn within angular error tolerance
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Mechanism II
• Dealing with errors– A new turn• Find out all route segments that are reachable by a turn
within the range: the reported angular displacement plus/minus angular error tolerance
– A new GPS coordinate• When a new GPS coordinate is available, check each
possible route by verifying whether the new GPS coordinate is within a certain distance: (distance error tolerance plus GPS error)
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Mechanism II
• Map-Matching algorithm– If no possible route exists• the system will restart by requesting a new GPS
coordinate– When a step and a turn arrive simultaneously• ignoring the steps during a turn
– When the number of possible routes becomes intolerable• request a GPS coordinate
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Evaluation
• Experiment– In each second • 50 accelerometer readings• 50 gyroscope readings • 1 GPS reading ???? Energy ????
• Tolerance setting– Distance error tolerance : 20 m– Angular error tolerance : 30°– Based on experience and haven’t been optimized
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Evaluation
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Evaluation
• Compare APT algorithm to:– Raw GPS coordinates tracking system – Combine the raw GPS coordinates with the map
information• In all three routes, our algorithm have
consistently less error– The most complicated route, contains more turns,
the error is 0 at most anchor points– The error at non-turn anchor points is at most 5m
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Evaluation
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Conclusion
• This paper present APT, a system targeting at accurate pedestrian localization
• Uses the accelerometer, gyroscope and GPS component of modern smartphones, and integrates them with map information
• Can tolerate GPS error and the different ways to hold the smartphone
• Achieve better performance than GPS only