Systems, Man & Cybernetics - April 2016 - 41

Table 2. Success rates in object recognition.
Object Type

Type I Data

Type II Data

Average

Stairway

0.967

0.900

0.933

Parallelepiped

1.000

0.933

0.967

Hallway

1.000

1.000

1.000

Doorway

0.933

0.867

0.900

Table

1.000

0.967

0.983

Monitor

0.900

0.800

0.850

Wall

1.000

1.000

1.000

Ground

1.000

1.000

1.000

CRC may steer into the desired direction of travel and thus
provide accurate guidance to a blind traveler. Three technology components-human-intent detection, pose estimation, and 3-D object recognition-have been developed to
enable wayfinding and obstacle avoidance by using a single
3-D imaging sensor. The design of the CRC takes into
account safety: if all robotic functions fail, the CRC

degrades itself into a white cane that can still be used as a
conventional mobility tool for navigation.
The CRC is in its development stage. We are working
with the orientation and mobility specialists and blind
trainees of the World Service for the Blind (Little Rock,
Arkansas) in designing and refining the CRC functions.
By the time of writing this article, we have just built and
tested two standalone systems, one for object detection
and the other for wayfinding. A speech interface was
used for human-device interaction. The object detector
is working properly at present, and it announces the
detection result when pointed toward a known object. In
our tests, we used single-frame range data for the sake of
real-time object detection. The wayfinding system locates
the user on a floor and guides the user to the destination
using the pose estimation method and the floorplan.
In the current tests, the CRC's starting point and the initial heading are assumed to be known. It was found that an
early orientation error created by the pose estimation method may accrue a big position error over time and make the
system out of work. A temporary solution was to extract the
wall from the range data and match the wall to the floorplan
to reset the error periodically. Using this scheme, the

(a)

(b)

Figure 8. Experimental results with a doorway, hallway, and box. (a) an intensity image. (b) a 3-D view of the detected

objects (stair in red, doorway in purple, hallway in blue, desk in light green, parallelepiped in green, grounds in black).

Ap ri l 2016

IEEE SyStEmS, man, & CybErnEtICS magazInE

41



Table of Contents for the Digital Edition of Systems, Man & Cybernetics - April 2016

Systems, Man & Cybernetics - April 2016 - Cover1
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