Here are two fascinating things that really stood out to me. The picture below [taken from this review] gives a schematic of the experiment showing that image flow is the key property that bees balance to navigate obstacles.
Analysis of the landing trajectories revealed that the flight speed of the bee decreases steadily as she approaches the surface. In fact, both the forward speed and the descent speed are approximately proportional to the height above the surface (Fig. 8), indicating that the bee is holding the angular velocity of the image of the surface approximately constant as the surface is approached. This strategy automatically ensures that both the forward and the descent speeds are close to zero at touchdown. Thus a smooth landing is achieved by an elegant and surprisingly simple process that does not require explicit knowledge of the bee's instantaneous speed or height (250).This analysis leads to two linear first order differential equations which can be solved to make predictions that the bee regulates its height to decrease exponentially with time. This is indeed observed to the case. [A colleague commented how the agreement between experiment and theory was much more impressive than the average biophysics research].
Srinivasan then went on to describe how some of these ideas are being implemented in algorithms for automated flight.
He stressed that his view was one should not follow a biomimetic strategy but rather a bio-princip one, i.e. finding what principles are used in nature [e.g. constant image flow] and using appropriately adapted implementations in artificial flight.