Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
Volume 34, Issue 8
Displaying 1-3 of 3 articles from this issue
  • —Comparison with Potential Method and Reinforcement Learning Method
    Seiji Aoyagi, Nobuhito Sato, Kyosuke Yamamoto, Tomokazu Takahashi, Mas ...
    2021 Volume 34 Issue 8 Pages 209-218
    Published: August 15, 2021
    Released on J-STAGE: November 15, 2021
    JOURNAL FREE ACCESS

    To coexist with human, a robot has to avoid obstacles based on human-like flexible decisionmaking. In this article, we recorded the angle and speed when a human operates a robot to avoid a moving obstacle on a developed computer simulator. Using obtained data, fuzzy rules to decide the moving direction and speed at every moment were derived as follows: as input variables, distance to obstacle, angle to obstacle, speed of obstacles, and moving direction of obstacle, were adopted. As output variables, steering angle and moving speed of robot were adopted, where it is noted not only angle but also speed is considered compared to other prior researches. Based on fuzzy-neural networks method, two networks having 4 inputs and 1 output were prepared. A membership function of input variable has 5 isosceles triangles. Fuzzy rules, number of which is 625 (=54), were assumed. Optimal center and width of each triangle were obtained so as that the network reproduces the trajectories of simulation experiment with minimum errors. The proposed method based on obtained fuzzy rules was compared with the conventional potential method and reinforcement trajectory learning method. The robot avoided flexibly and smoothly a moving obstacle like human with both short mileage and small crash rate by using proposed method on the simulator.

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  • Hirofumi Masui, Takahiro Oshima, Kazuki Nakabayashi, Eisuke Nagahashi, ...
    2021 Volume 34 Issue 8 Pages 219-230
    Published: August 15, 2021
    Released on J-STAGE: November 15, 2021
    JOURNAL FREE ACCESS

    Dealing Rights to Speak (DRS) is a communication-field mechanism enabling people to manage speech order in a decentralized manner. However, the method was evaluated only in small face-toface meetings where less than five people attended. In this paper, we analyze the effect of DRS when it is applied to a meeting where a large number of people, e.g., more than 10, are attending. For this purpose, we first developed a mobile application with which many people can use DRS in their discussions. We performed an experiment with four conditions, i.e., 4 participants with and without DRS and 16 participants with and without DRS. We compared the four conditions in both a subjective and an objective manner. The results show that the effect of DRS on a large number of people is similar to that of a small number of people. Also, some other findings were newly observed. It was shown that the number of “filler” is increased when people use DRS. It was shown that the quality of the meetings tends to degrade when the number of participants increases without any communication-field mechanism though DRS can mitigate the negative effect.

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  • Yamato Mihara, Naoyuki Hara, Keiji Konishi
    2021 Volume 34 Issue 8 Pages 231-233
    Published: August 15, 2021
    Released on J-STAGE: November 15, 2021
    JOURNAL FREE ACCESS
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