人工知能学会第二種研究会資料
Online ISSN : 2436-5556
2023 巻, SAI-047 号
第47回社会におけるAI研究会
選択された号の論文の2件中1~2を表示しています
  • 鈴木 宏哉, 上原 温揮, 藤澤 丈, 前田 綾也, 松永 一希, 安藤 圭祐, 内種 岳詞, 岩田 員典, 伊藤 暢浩
    原稿種別: 研究会資料
    2024 年 2023 巻 SAI-047 号 p. 03-
    発行日: 2024/03/01
    公開日: 2024/04/19
    研究報告書・技術報告書 フリー

    RRS (RoboCupRescue Simulation) is a disaster relief simulation for urban earthquakes. The RRS has some rescue tasks and some kinds of agents to solve them. This simulation must determine a proper assignment between agents and rescue tasks to rescue civilians as much as possible. It is important for such a disaster relief problem to consider the rescue order of the tasks and time constraints of the tasks and to cooperate among some kinds of agents. This study models the disaster relief problem of RRS with order and time constraints as the Layered DCOP (L-DCOP). The L-DCOP is an extension of DCOP whose definition includes order and time constraints. We designed and implemented disaster relief agents that solve the L-DCOP in RRS. As a result of some simulations under various conditions, we confirmed that some kinds of agents could cooperate appropriately based on the order and time constraints.

  • 畠山 響, 中田 光紀, 下田 萌喜, 中島 智晴, 楠木 祥文, 秋山 英久
    原稿種別: 研究会資料
    2024 年 2023 巻 SAI-047 号 p. 05-
    発行日: 2024/03/01
    公開日: 2024/04/19
    研究報告書・技術報告書 フリー

    In the realm of soccer, a substantial amount of data analysis has been undertaken. Although analyses using tracking data are prevalent, those involving gaze information have not progressed as much due to the challenges associated with measuring gaze. However, in soccer, gaze and visual information are critical features for players when making situational judgments. Concurrently, gaze tracking technology utilizing virtual reality (VR) has been advancing.In this study, we recreated logs of soccer simulation 2D games by converting into 3D models for more realistic visualization. We not only reproduced the positional information available from simple logs into the 3D model but also created cameras representing each player's viewpoint and performed Z-axis interpolation to replicate an environment that closely resembles real-world soccer. Subsequently, we conducted a survey with participants, comparing 2D and 3D models. Although the survey revealed numerous challenges, the 3D model developed was a step closer to acquiring the field of view information of experts, akin to a real soccer environment.The paper also describes some directions of future research which may include data augmentation with actual soccer data and extending this 3D model to VR, enabling gaze measurement. Ultimately, it is conceivable that analyzing the gaze movements as perceived by experts and implementing them into the player model of robot soccer could become feasible.

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