UCLA ENGINEERING Computer Science
Indoor Localization and Navigation of Wheelchair Users with Smartphones
Ruolin Fan, Silas Lam, Emanuel Lin, Oleksandr Artemenkoⱡ, Mario GerlaUniversity of California, Los Angeles (UCLA)
{ruolinfan, silaslam, emanuel, gerla}@cs.ucla.eduⱡIlmenau University of Technology
UCLA ENGINEERING Computer Science
Outline
• Introduction• Background• System Design• Implementation• Evaluation• Conclusion
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 Computer Science
Inferring Movements (Cont’d)
• General Turns• One wheel moves faster than the other• Derive equation using radians• , • And therefore• • In degrees,•
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 Computer Science
Improving Turn Accuracyassuming blue print is known
• Right angle correction• Assume 90 degree turns
when the turning angle is close to it
• Correction via boundary detection• Detect building
boundary and make corrections accordingly
Projected results 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!