Altshuler Douglas L, Srinivasan Mandyam V
Department of Zoology, University of British Columbia, Vancouver, BC, Canada.
Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia.
Front Neurosci. 2018 Mar 16;12:157. doi: 10.3389/fnins.2018.00157. eCollection 2018.
Over the last half century, work with flies, bees, and moths have revealed a number of visual guidance strategies for controlling different aspects of flight. Some algorithms, such as the use of pattern velocity in forward flight, are employed by all insects studied so far, and are used to control multiple flight tasks such as regulation of speed, measurement of distance, and positioning through narrow passages. Although much attention has been devoted to long-range navigation and homing in birds, until recently, very little was known about how birds control flight in a moment-to-moment fashion. A bird that flies rapidly through dense foliage to land on a branch-as birds often do-engages in a veritable three-dimensional slalom, in which it has to continually dodge branches and leaves, and find, and possibly even plan a collision-free path to the goal in real time. Each mode of flight from take-off to goal could potentially involve a different visual guidance algorithm. Here, we briefly review strategies for visual guidance of flight in insects, synthesize recent work from short-range visual guidance in birds, and offer a general comparison between the two groups of organisms.
在过去的半个世纪里，对苍蝇、蜜蜂和飞蛾的研究揭示了许多用于控制飞行不同方面的视觉引导策略。一些算法，比如在向前飞行中使用模式速度，是迄今为止所有被研究昆虫都会采用的，并且被用于控制多种飞行任务，如速度调节、距离测量以及在狭窄通道中定位。尽管鸟类的远程导航和归巢受到了很多关注，但直到最近，人们对鸟类如何时刻控制飞行却知之甚少。一只鸟如往常那样迅速穿过茂密的枝叶降落在树枝上时，就如同参与一场真正的三维障碍滑雪，它必须不断躲避树枝和树叶，实时找到甚至可能规划出一条无碰撞的通往目标的路径。从起飞到抵达目标的每一种飞行模式都可能涉及不同的视觉引导算法。在这里，我们简要回顾昆虫飞行视觉引导的策略，综合鸟类短程视觉引导的最新研究成果，并对这两类生物进行总体比较。
