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    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/122099
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/122099

    Title: Choosing autonomy modes for multirobot search
    Authors: 簡士鎰
    Chien, Shih Yi
    Lewis, Michael;Wang, Huadong;Chien, Shih Yi;Velagapudi, Prasanna;Scerri, Paul;Sycara, Katia
    Contributors: 資管系
    Date: 2010-05
    Issue Date: 2019-01-23 11:50:46 (UTC+8)
    Abstract: Objective: The number of robots an operator can supervise increases with the robots’ level of autonomy. The reported study investigates multirobot foraging to identify aspects of the task most suitable for automation. Background: Many envisioned applications of robotics involve multirobot teams. One of the simplest of these applications is foraging, in which robots are operated independently to explore and discover targets. Depending on levels of autonomy and task, operators have been found able to manage 3 to 12 robots. Method: The foraging task can be functionally subdivided into visiting new regions and identifying targets. In the reported experiment, full-task foraging performance was compared with exploration and perceptual search performance for 4-, 8-, and 12-robot teams in a between-groups repeated measures design. Results: Operators in the full-task condition could not successfully manage 12 robots, finding only half as many victims as perceptual search operators. Exploration performance was roughly the same in the full-task and exploration conditions, suggesting that performance of this subtask was limiting the number of robots that could be controlled. Conclusion: Performance and workload measures indicate that exploration (navigation) tasks are the limiting factor in multirobot foraging. This finding suggests that robot navigation is the best candidate for automation. Application: Search tasks, such as foraging or perimeter control, account for many of the near-term applications envisioned for multirobot teams. The results support the choice of task-centered architectures in which the control and coordination of robotic platforms is automated, leaving search and identification of targets to human operators.
    Relation: Human Factors: The Journal of the Human Factors and Ergonomics Society, 52(2), 225-233
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1177/0018720810366859
    DOI: 10.1177/0018720810366859
    Appears in Collections:[資訊管理學系] 期刊論文

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