UCLA ENGINEERING
Computer Science
Indoor Localization and Navigation
of Wheelchair Users with
Smartphones
Ruolin Fan, Silas Lam, Emanuel Lin, Oleksandr Artemenkoⱡ, Mario Gerla
University of California, Los Angeles (UCLA)
{ruolinfan, silaslam, emanuel, gerla}@cs.ucla.edu
ⱡIlmenau University of Technology
oleksandr.artemenko@tu-ilmenau.de
UCLA ENGINEERING
Outline
•
•
•
•
•
•
Introduction
Background
System Design
Implementation
Evaluation
Conclusion
Computer Science
UCLA ENGINEERING
Computer Science
Introduction
• GPS does not work indoors
• Lack of satellite signals
• Need an alternative way to position ourselves
indoors
• Try to utilize unique features pertaining to
wheelchairs
• Transform measured wheel rotations into both
distance and angular displacement
• Crowd sourcing popular wheelchair access paths
• Useful for blind/impaired wheelchair riders
UCLA ENGINEERING
Computer Science
Background: Indoor Localization
• Triangulation methods from cellular, WiFi, or
acoustic (Signal strength or signature)
• Require landmark placement knowledge, previous
mapping of the site; affected by obstacles
• Dead reckoning
• Compute the current position based on a
previously known position and incremental
displacement
• Can complement and rescue GPS and
triangulation methods (eg Autogait[Percom 10])
UCLA ENGINEERING
Computer Science
Wheelchair Dead Reckoning - Overview
• Get initial position of the wheelchair via GPS
coordinates or other means
• Mark the wheels on the wheelchair at each spoke
• Track the wheelchair’s movements by counting
rotations of the wheels using the marks (a “tick”)
• Simple model (perfect traction, no sliding):
• If wheels rotate at the same rate => straight
movement
• If wheels rotate at different speeds => turns
UCLA ENGINEERING
Computer Science
Inferring Movements
• Straight forward movement:
• Both wheels move at the same rate
•
• cwheel: the wheel’s circumference
• n: the number of marks on each wheel
• Sharp turns:
•
•
•
•
•
•
One wheel is moving while the other stays still
wchair: the width of the wheelchair
cchairTurn: The circumference when the chair turns a full circle
dtravelled: The distance travelled by the turning wheel
UCLA ENGINEERING
Inferring Movements (Cont’d)
• General Turns
•
•
•
•
•
•
•
One wheel moves faster than the other
Derive equation using radians
,
And therefore
In degrees,
Computer Science
UCLA ENGINEERING
Computer Science
Implementation
• Wheelchair Specifications
• 8 magnets per wheel
• 1 reed switch per wheel
• Reed switches connected to
Bluetooth mouse
• When magnet moves close
to reed switch, it trigger a
mouse click event
UCLA ENGINEERING
Computer Science
Implementation (Cont’d)
• Translate left/right mouse clicks to
distance/direction traveled
• Base calculations on physical wheelchair
measurements
• Implemented straight movement and sharp turns
• Clicks detected by JavaScript in web browser
• Events are sent via AJAX to PHP server and
MySQL database
• Visualize wheelchair movement on a map
UCLA ENGINEERING
Computer Science
Implementation Challenges
• Wheels are not always synchronized together
• Magnets are far apart from one another
• Result: coarse-grained data
• Wheels may “slip” due to physical
imperfections
UCLA ENGINEERING
Computer Science
Our Solution (can you explain better
please??)
• Find ways to do “approximately equals”
• Made our own low-pass filter in counting the
clicks
• Single values that look like (1,0) would behave
like (1,1), and pairs like (1,0),(0,1) would also
behave like (1,1)
• Count small turns as straight movements until
confirmed to be a turn
• When a turn is confirmed, backtrack the last
forward movement and aggregate the turn
UCLA ENGINEERING
Computer Science
Example Forward
+-----------+-------+-----------------+
| time
| state | magnitude
|
+-----------+-------+-----------------+
| ...
| ...
|
... |
| 855742327 | F
|
0.9106 |
| 855743328 | F/R
|
1.13825 |
| 855744328 | F
|
0.9106 |
| 855745328 | F
|
0 |
| 855746327 | F/L
|
1.13825 |
| 855747352 | F
|
0.9106 |
| 855748332 | F/L
|
1.13825 |
| 855749332 | F
|
0.9106 |
UCLA ENGINEERING
Computer Science
Example Turn
+-----------+-------+-----------------+
| time
| state | magnitude
|
+-----------+-------+-----------------+
| ...
| ...
|
... |
| 855713328 | F/L
|
0.22765 |
| 855714328 | F
|
0.22765 |
| 855715329 | L
| 49.245283018868 |
| 855716329 | L
| 24.622641509434 |
| 855723329 | L
| 24.622641509434 |
| 855726328 | F
|
0.68295 |
| 855727328 | F/L
|
0.9106 |
Total turn = 98.49 degrees
UCLA ENGINEERING
Computer Science
Evaluation - General Movements
• Move the wheelchair
around Boelter Hall 3rd
floor, the main engineering
building at UCLA
• Straight forward movement
is accurate
• Turns are off
• Only 8 magnets on a wheel:
can only measure degrees in
increments of 24.5
• The closest to a 90 degree
turn is 98 degrees
UCLA ENGINEERING
Computer Science
Evaluation – Straight Movements
Error Rate vs. Travelling Speed
UCLA ENGINEERING
Computer Science
Evaluation – Straight Movements (Cont’d)
Error Rate vs. Update Period (Fast Travelling Speeds)
UCLA ENGINEERING
Improving Turn Accuracy
Computer Science
assuming blue print is known
• Right angle correction
• Assume 90 degree turns
when the turning angle
is close to it
Projected results
• Correction via boundary
detection
• Detect building
boundary and make
corrections accordingly
Projected results
UCLA ENGINEERING
Computer Science
Conclusions
• Indoor localization with a wheelchair can be
accomplished by translating wheel rotation
measurements into distance and direction
• Accuracy is high for slow to medium speeds, but
decreases as speed goes up
• Improvements can be made by simply adding
magnets
• Successful proof of concept project
UCLA ENGINEERING
Computer Science
Future Work
• Improve the accuracy by exploiting existing
smartphone sensors:
• Compass, altimeter (in a multilevel building),
gyroscope, accelerometer
• Synergize wheelchair dead reckoning with
WiFi signature methods
• The wheelchair is used as surveyor, to calibrate
the signatures
UCLA ENGINEERING
Computer Science
Thank You!