NSF Postdoctoral Fellowship in Biology FY 2012

发现路径和规划机动：鸟类如何在复杂的杂乱世界中飞行动物经常以高速在森林、城市环境和其他非常复杂的环境中飞行。这些飞行要求：1）对周围环境的快速视觉识别，2）快速准确地规划无障碍路径，以及3）准确的机动。这三个行为是相互依赖的：视觉通知路径规划，定义要执行的机动，其执行呈现一个新的场景。尽管有很长的研究历史，试图了解鸟类如何处理视觉信息，规划路径，以及它们机动的空气动力学，但很少有研究探索这些方面如何在真实的世界中共同发挥作用。这项工作是调查视觉之间的反馈，路径规划，并在真实的世界中的气动机动。这位研究员正在开发一种仪器，鸽子（Columba livia）可以在自由飞行时携带在背包中。该仪器由视频设备和惯性传感器（伊穆斯）组成，将使研究人员能够记录机翼运动学数据，视觉环境数据以及通过自然环境进行长时间户外飞行的飞行路径。作为这项工作的一部分，该研究员将通过哈佛生命科学为高中生物教师提供有关最新进展的讲座。外展计划，并为哈佛自然历史博物馆制作展览材料，重点是成功的生物飞行所需的机制。此外，对这些自然过程的进一步了解将为未来生产完全或部分自主微型飞行器的工程工作提供信息。

Spotting paths and planning maneuvers: How birds fly through a complex cluttered worldFlying animals regularly navigate through forests, urban settings, and other very complex environments at high speeds. These flights require, 1) rapid visual recognition of the surrounding environment, 2) quick and accurate planning of unobstructed paths, and 3) accurate maneuvers. These three behaviors are interdependent: vision informs path planning which defines the maneuvers to be performed whose execution presents a new scene. Despite a long history of work seeking to understand how birds process visual information, plan paths, and the aerodynamics of their maneuvers, little work has explored how these aspects work together in the real world. This work is investigating the feedback between vision, path planning, and aerodynamic maneuvering in the real world. The fellow is developing instrumentation which pigeons (Columba livia) can carry in backpack-harnesses during free flight. This instrumentation, consisting of video devices and inertial sensors (IMUs), will allow researchers to record wing kinematic data, visual environment data, and flight paths over long outdoor flights through natural environments. As part of this work, the fellow will offer lectures on recent advances to high school biology teachers through Harvard Life Sciences? Outreach Program, and develop exhibit material for the Harvard Museum of Natural History focusing on the mechanisms required for successful biological flight. Additionally, increased understanding of these natural processes will inform future engineering efforts to produce fully or partially autonomous micro aerial vehicles.