Oita Prefectural College of Arts and Culture

Abstract Developers of museum service systems want to know what users think about their systems and they often design questionnaires to capture users' opinions. However, there are usually serious gaps between what developers want to know and what the users really think about the system. The present research aims to develop a questionnaire that takes into consideration the user's point of view, including opinions of people who do not want to use the system. We put the plan into practice by gathering opinions such as feelings, demands, and expectations about the systems from the general public.

従来, 音声認識技術を用いたロボットの遠隔操作システムでは語彙データのためのディスク資源や認識のためのCPU資源など, 高性能のコンピュータが要求される。しかし, 操作者がモバイル環境にいる場合や複数の部屋を移動する場合には, 端末へのソフトウェアのインストールや端末の持ち運びなどが困難である。そこで本研究では, 3層アーキテクチャを採用した移動ロボットシステムを開発し, シン・クライアントを用いた音声による遠隔操作環境を実現する。

In the last decade, many sensor-based navigation algorithms have been proposed, which keep convergence of a mobile robot to its destination in a 2-D uncertain environment. From the convergence viewpoint, all the previous algorithms are categorized into three types, i.e., metric, topologic, and geometric algorithms. A mobile robot supervised by each algorithm frequently joins a limit cycle (deadlock) if the robot generates position, orientation, and/or sensor errors. Especially, geometric and topologic algorithms are theoretically damaged by position and sensor errors, respectively, even though they are small enough in a 2-D unknown environment. Therefore, we are obliged to rely upon the metric algorithm if all errors exist. In case that a mobile robot is ready for position, orientation, and sensor errors, we propose a stable metric sensor-based navigation algorithm for overcoming all the errors. The stable algorithm always leads a robot near its destination in a sparse environment whose minimum distance of obstacles is sufficiently larger than the sum of a radius of a mobile robot and position ingredients of the errors. Finally, we ensure convergence of a robot in destination's neighborhood in the proposed algorithm by theoretical proof and experimental result.