NSF Postdoctoral Fellowship in Biology FY 2012

发现路径和规划机动：鸟类如何在复杂杂乱的世界中飞行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。这些飞行需要，1)对周围环境的快速视觉识别，2)快速准确地规划无阻碍的路径，以及3)精确的机动。这三种行为是相互依赖的：视觉为路径规划提供信息，路径规划定义了要执行的操作，其执行呈现了一个新场景。尽管研究鸟类如何处理视觉信息、规划路径和飞行的空气动力学已有很长的历史，但很少有研究探索这些方面在现实世界中是如何协同工作的。这项工作是研究现实世界中视觉、路径规划和空气动力学机动之间的反馈。这位研究员正在开发一种仪器，鸽子（Columba livia）可以在自由飞行时用背包背带携带。该仪器由视频设备和惯性传感器（imu）组成，将使研究人员能够记录机翼运动数据、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，他将通过哈佛生命科学学院为高中生物教师讲授最新进展。外展计划，并为哈佛自然历史博物馆开发展览材料，重点关注成功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的工程努力提供信息，以生产完全或部分自主的微型飞行器。

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.