四旋翼飞行器自动控制竞赛作为跨学科设计教育的一个例子

C. Nitschke, Y. Minami, Masayuki Hiromoto, Hiroaki Ohshima, Takashi Sato
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引用次数: 21

摘要

随着低成本微型飞行器(MAVs)的出现,无人驾驶飞行器(uav)的应用越来越广泛。机器人是一个受欢迎的跨学科教育目标,因为它涉及到多个学科的理解和合作。因此,无人机可以作为一个理想的研究平台。然而,由于机器人技术需要技术背景、技能和最初的努力,它通常应用于长期课程。在本文中,我们成功地利用了机器人在短期教育中的相反情况,为没有背景的学生提供了为期一天的自动视觉无人机导航竞赛。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任务和缺乏技术方面。我们引入了一种新颖的开源编程库,其中包含指导经验学习的程序,并允许快速开发。它通过新颖的嵌套标记设计和从14个Parrot AR.Drone 2.0前置摄像头估计的准确校准参数,为基于标记的跟踪做出了贡献。我们展示了对比赛结果的详细讨论,这代表了关于机器人教育和图书馆有效性的广泛用户研究。在复杂学科中实现陡峭的学习曲线对跨学科设计教育具有重要意义,因为它允许深入了解潜力和局限性,以促进决策,非常规问题解决方案和新颖应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A quadrocopter automatic control contest as an example of interdisciplinary design education
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.
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