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Chen et al. Intell Robot 2023;3:420-35 https://dx.doi.org/10.20517/ir.2023.24 Page 432

Figure 16. Set-up of walking experiments. (A) Objects situated at a distance less than 2 m away; (B) Objects situated between 2 m and
4 m.

The success rate is calculated for each directional and distance instruction given in these two experiments.
For example, if the system gives a left indication when it should turn left, it is counted as a success, and the
opposite or no indication is counted as a failure. As for the distance, the system provides a faster vibration if
the object is within 2 m, and the system counts it as a success if it produces the correct vibration pattern for
each distance. In the case of multiple objects, a success was counted if all of the obstacles were passed in one
pass, and a failure was counted if all of the obstacles were not passed. The experiment was conducted 20
times in each case. The results are summarized in Tables 4 and 5. In the obstacle experiment, the estimation
time for the entire system was within 0.7 s, which was considered sufficient as a support system for a
visually impaired person in consideration of walking speed.

4. DISCUSSION
The results in Tables 4 and 5 show that the successful recognition rate was high for a single object and
comparatively low for multiple objects. As explained in Section 2.4, the reason for this is that the matching
method was performed for each object on the camera screen to measure the distance based on parallax,
which increased the amount of calculations needed when there were multiple objects. The calculations
could not keep up with the frame rate. In addition, in regard to the accuracy of the face detection, as the
number of objects increased, the overall probability of correct detection also decreased. Moreover, the
results when obstacles were within a distance of 2 m were better than those over 2 m away. This was because
the detection by YOLO became less accurate in the range of 2 m or more due to resolution issues, and the
system switched to using skin color detection.

As for the tactile part, users successfully avoided objects by referring to the presented vibration patterns
given by the motors and SMA actuators in the glove. The distance information presented through the
various vibration frequencies and their patterns also properly worked. In the experiment, for example, when
the left motor vibrated quickly, that indicated that there was an obstacle within a 2-meter distance, and the