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A quadrocopter automatic control contest as an example of interdisciplinary design education

机译:作为跨学科设计教育的示例,一场二峰自动控制竞赛

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Unmanned aerial vehicles (UAVs) have many applications and quickly gain popularity with the availability of low-cost micro aerial vehicles (MAVs). Robotics is a popular interdisciplinary education target as it involves understanding and collaboration of several disciplines. Thus, UAVs can serve as an ideal study platform. However, as robotics requires technical background, skills and initial efforts, it is commonly applied in long-term courses. In this paper we successfully exploit the opposite case of robotics in short-term education for students without background, in form of a one-day contest on automatic visual UAV navigation. We provide an extensive survey, and show that existing material and tools do not fit the task and lack in technical aspects. We introduce a novel open-source programming library that comprises programs to guide learning by experience and allow rapid development. It makes contributions to marker-based tracking, with a novel nested-marker design and accurate calibration parameters estimated from 14 Parrot AR.Drone 2.0 front cameras. We show a detailed discussion of the contest results, which represents an extensive user study regarding robotics in education and the effectiveness of the library. The achievement of a steep learning curve for a complex subject has important implications in interdisciplinary design education, as it allows deep understanding of potentials and limitations to facilitate decision-making, unconventional problem solutions and novel applications.
机译:无人驾驶飞行器(UAV)有许多应用程序和低成本的微型飞行器(微型飞行器)的可用性,迅速得到普及。机器人是一种流行的跨学科教育的目标,因为它涉及的理解和几个学科的协作。因此,无人机可以作为一个理想的学习平台。然而,随着机器人需要技术背景,技能和最初的努力,它常用于长期应用的课程。在本文中,我们成功地利用在学生短期教育机器人的相反的情况下没有背景,在自动视觉无人机导航了为期一天的比赛形式。我们提供了一个广泛的调查,并表明,现有的材料和工具不适合的任务,缺乏技术方面的问题。我们引入新的开源编程库,包括程序,以指导由经验中学习,并允许快速发展。它使基于标记物跟踪贡献,具有新颖嵌套标记设计和精确的校准参数从14台鹦鹉AR.Drone的2.0前摄像机估计。我们展示了比赛结果的详细讨论,这代表关于教育机器人和图书馆的有效性广泛的用户研究。对于一个复杂的问题一个陡峭的学习曲线的实现具有跨学科的设计教育的重要意义,因为它允许潜力和局限的深刻理解,以促进决策,非常规的解决问题的方法和新的应用。

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