1. Assisted Navigation
for an Autonomous Wheelchair
for the Severely Disabled
Xinyi Gong1
Mathieu Labbé2, Vivek Burhanpurkar3
Jonathan Kelly4
1Division of Engineering Science,
University of Toronto, Toronto;
2IntRoLab laboratory, Interdisciplinary Institute of
Technological Innovation (3IT),
Université de Sherbrooke, Sherbrooke;
3Cyberworks Robotics Inc., Orillia;
4Space & Terrestrial Autonomous Robotics Systems
(STARS) laboratory, Institute for Aerospace Studies,
University of Toronto, Toronto

2. Background
 Electric-powered wheelchair by Pride Mobility
 Visual Simultaneous Localization And Mapping (vSLAM)
implemented by Mathieu Labbé (PhD, Université de
Sherbrooke)
 Path planning and autonomous navigation algorithms
available on Robotics Operating System (ROS)
 Integrated with and designed the wheelchair’s driving and
sensing system by Charlie Guan (EngSci 1T6 + PEY) with
core values including:
o Use only low-cost consumer-grade hardware and sensors
o Reliability & Accuracy

3. The Wheelchair
Kinect v2
Rotary Encoder
SCIM Controller
Touchscreen
Display
Arduino & Circuits
Gigabyte Brix
Compact PC

4. Further work on…
Autonomous navigation + vSLAM
o Require pre-mapping the environments
o Maps saved in database
 When map is used for autonomous navigation, user selects a
location & direction on map
 Hence only useful for often visited places (e.g., home, office,
favourite coffee shop)
Time Consuming
Memory & Storage

5. My Approach
Alternative to Pre-mapping – Incremental Goal Generation
o Autonomous navigation + vSLAM still on
o Maps cleared with radius
 Save memory and storage
 Provide a buffer of information of previously unseen
spaces
 Using the buffer, incremental goals are generated to
keep it moving with limited knowledge about the
environment

6. Assistive Mode using Incremental Goal Generation
Door Traversal
Desk Docking
 Navigation through tight spaces requires sophisticated path
planning and accurate operation
 Limitations in their own motor control
Corridor & Wall Following
 Long period of joystick operation is difficult to sustain for the
severely disabled

7. Door Traversal
Most papers discussing door traversal only considered the
most basic scenario: a door in the middle a flat wall

8. Door Traversal
A simple Google Image search gives another common one:
http://www.chateauwaters.com/cw/apartment-homes/floorplans/

9. Door Traversal
A more complex scenario:

10. Corridor & Wall Following
When both walls within field of view (FOV) of camera, drive in-between.
When only a single wall is available, follow it with a reasonable distance.
At a corner by two walls, turn corresponding degrees and keep following.
Stop when no further information is available.

11. Desk Docking
• Work in progress
• Tested in real-world
3D sensor reading
• Detect desktop as a
surface
• Remove desktop to
analyze under-desk
space and calculate a
potential location and
orientation

12. Progress & Up Next
• So far, door traversal and corridor following have been tested in
real-world environment. Although successful experiments have
been repeated for considerable number of times, several
improvements are required and under investigation.
• Desk docking will be tested next.
• Will test in a variety of spaces on UofT campus by the end of
summer, 2016.
• End goal: demonstrate a 4-hour, failure-free supervised run of
the wheelchair without a passenger. If successful, further testing
will follow.

13. Thank you for listening !