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Nocturnal Visual Orientation in Flying Insects: A Benchmark for the Design of Vision-based Sensors in Micro-Aerial Vehicles

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Final rept. 15 Apr 2008-15 Oct 2010

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In flying organisms such as insects, the sensory modalities that are available for flight control and navigation are more constrained than is the case in man-made aircraft. Insects do not carry radio communications equipment, radar, GPS, infrared sensors or large precision inertial systems, but rather get by with an assembly of conventional senses such as vision, mechanoreception, hearing and chemoreception. However, this sensor assembly, together with the information processing circuitry of the insect brain, is extremely miniaturized in comparison to any existing technical systems. Furthermore, each of these sensory systems has been under evolutionary selective pressure for the optimisation of its sensitivity and acuity. The visual sense, in particular, has often been adapted to the extreme limit of the physically possible. Our research aimed to improve our knowledge in the general field of animal navigation and flight control, with a view towards applications in guided ammunition and Micro Aerial Vehicles MAVs. Specifically, examined the physical limits of vision-based navigation and attitude control in insects. A first key topic addressed is the lower limit of light intensity at which insects are capable of using vision for obstacle detection and flight attitude control. A second topic is the elucidation of the neural principles that are responsible for this performance. A third topic is the lower limit to which polarised skylight is usable as a compass cue for navigation, both in terms of intensity and degree of polarisation. The identification of the critical parameters used by nocturnal insects for navigation and flight stabilisation in dim light will help us to identify the neural networks that are responsible. This in turn will allow the development of computational algorithms that analyse celestial cues for dim light navigation and flight stabilisation systems in machines.

Subject Categories:

  • Flight Control and Instrumentation
  • Biology
  • Air Navigation and Guidance

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