Insects are capable of robust visual navigation in complex environments using efficient information extraction and processing approaches. This paper presents an implementation of insect inspired visual navigation that uses spatial decompositions of the instantaneous optic flow to extract local proximity information. The approach is demonstrated in a corridor environment on an autonomous quadrotor micro-air-vehicle (MAV) where all the sensing and processing, including altitude, attitude, and outer loop control is performed on-board. The resulting methodology has the advantages of computation speed and simplicity, hence are consistent with the stringent size, weight, and power requirements of MAVs.

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The well-known Rayleigh-Taylor (RT) and Richtmyer-Meshkov (RM) instabilities characterize the behavior of flows where two gases (or fluids) of different densities mix due to gravity (RT) or due to impulsive acceleration (RM). Recently, analogous instabilities have been observed in two-phase flows where the seeding density of the second phase, e.g., particles or droplets in gas, and the resulting average density, is initially non-uniform. The forcing causes the second phase to move with respect to the embedding medium. With sufficient seeding concentration, this leads to entrainment of the embedding phase. The resulting movement is similar to the movement that would evolve in a mixing flow with no second phase seeding, but with non-uniform density (not unlike a mixture of lighter and heavier gases), where RT and RM instabilities develop in the case of gravityinduced and impulsive acceleration, respectively. The hydrocode SHAMRC has been used in the past to study the formation and growth of the RM instability. Here we attempt to use it to model the first order formation and growth phenomena of the new class of instability in two-phase flows first, by approximating the second phase as a continuous fluid with an averaged density, and second, by taking the relative motion of particles (droplets) into account explicitly. The initial conditions are varied to provide a wide range of instability growth rates. Comparison of the numerical results with experiment shows good agreement.

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