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首页> 外文期刊>The International journal of robotics research >Perching with a robotic insect using adaptive tracking control and iterative learning control
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Perching with a robotic insect using adaptive tracking control and iterative learning control

机译:使用自适应跟踪控制和迭代学习控制与机器人昆虫共栖

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摘要

Inspired by the aerial prowess of flying insects, we demonstrate that their robotic counterpart, an insect-scale flapping-wing robot, can mimic an aggressive maneuver seen in natural fliers-landing on a vertical wall. Such acrobatic movement differs from simple lateral maneuvers or hover, and therefore requires additional considerations in the control strategy. In this paper, we propose a single-loop adaptive tracking flight control suite designed with an emphasis on the ability to track dynamic trajectories, and an iterative learning control algorithm to account for unmodeled dynamics and systematic errors for improved landing accuracy. Magnets were chosen to enable attachment to the vertical surface due to their simplicity. The proposed controller was verified in a series of hovering and aggressive translational flights. Furthermore, we show that by learning from previous failed attempts, the biologically-inspired robot could successfully perch on a magnetic wall after eight learning iterations.
机译:受飞行昆虫的超凡能力的启发,我们证明了它们的机器人对等物,一种昆虫规模的拍打翼式机器人,可以模仿自然飞行物着陆时在垂直墙上着陆时的激进动作。这种杂技运动不同于简单的侧向操纵或悬停,因此需要在控制策略中进行其他考虑。在本文中,我们提出了一种单环自适应跟踪飞行控制套件,该套件的设计着重于跟踪动态轨迹的能力,以及一种迭代学习控制算法来解决未建模的动力学和系统误差,以提高着陆精度。由于其简单性,选择了磁体以使其能够附着在垂直表面上。拟议中的控制器在一系列悬停和激进的平移飞行中得到了验证。此外,我们表明,通过从先前的失败尝试中学习,受生物启发的机器人可以在八次学习迭代后成功地栖息在磁性墙上。

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