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Page 421 Chen et al. Intell Robot 2023;3:420-35 https://dx.doi.org/10.20517/ir.2023.24

1. INTRODUCTION
There are 36 million visually impaired people in the world, according to a report from BBC News Japan in
[1]
2017 . The number is anticipated to triple by 2050 due to our aging society. The percentage of people who
are blind or have difficulty seeing is exceptionally high in South Asia and sub-Saharan Africa, making life
even more inconvenient in developing countries. There are also 300,000 visually impaired people in Japan;
thus, it is important to make the daily lives of the visually impaired easier through studies of assistive
technology.

For example, Dionisi et al. developed a wearable object detection system to help the visually impaired using
Radio Frequency Identification(RFID) . The system detects tagged objects, and the strength of the signal is
[2]
used to estimate its direction and distance from the user. Tags are detected at home easily; however, in the
case of using the system in an outside environment, it is difficult to detect tags and for computer devices to
execute the system.

Wagner et al. developed a tactile display by using metal pins and servomotors . Each pin has a diameter of
[3]
1mm and is arranged in a 6 × 6 array. The display presents the tactile information of small objects since the
metal pins are able to present vibratory information with frequencies up to 25 Hz. Servomotors are tightly
packed together to achieve spacing between pins of 2 mm, and these pins can be vibrated up and down by
rotating the servomotors. The large volume and the large number of motors needed to move the pins,
however, make the stack of motors taller and less wearable.

[4]
Mukhiddinov et al. developed smart glasses for the visually impaired . With these glasses, they employed a
deep learning model for object detection, character recognition, and tactile presentation to provide
information about the surrounding environment. The system uses a camera, a GPS sensor, and an
ultrasonic sensor for information sensing. The deep learning model analyzes the images acquired by the
camera to detect objects and characters. The ultrasonic sensor calculates the distance to the object and
presents this information through the tactile display installed in the glasses.

Shen et al. developed a wearable system using object recognition and SMA actuators . This research
[5]
realized real-time object recognition by using a compressed YOLO network and presented the information
using a small camera and tactile actuators . The tactile presentation allows a user to know which direction
[5]
to go to avoid an obstacle. In addition, since it was developed as a wearable system that uses Raspberry Pi, it
is highly portable. Based on this research, we also consider the importance of providing information
regarding the distance from a user to various obstacles through tactile patterns that provide alerts and
avoidance information. In our study, we try to develop a new function for distance measurements.

Ashveena et al. developed a portable camera-based identification system for visually impaired people .
[6]
They introduced an algorithm to detect and recognize objects by using the SSD algorithm, a single camera,
and an ultrasonic sensor. They introduced voice guidance through earphones as a means of communication
with the visually impaired. The advantage of this system is its compactness, meaning that it can be executed
with a microcomputer. However, precise distance measurements for multiple obstacles are difficult to carry
out due to the limitations of the ultrasonic sensor. In addition, the use of earphones will disrupt the auditory
system of users, making it difficult for them to pay attention to their surrounding environment.

In this study, we propose a system that recognizes obstacles in real time and presents tactile information,
including the direction of the obstacle and the distance to the obstacle, through a wearable system. We
introduce a tactile glove that presents this information through vibratory patterns. The tactile glove presents