  Our goal in this work is to expand the theory and practice of robot
locomotion by addressing critical challenges associated with the robotic
biomimicry of bat aerial locomotion. Bats are known for their pronounced, fast
wing articulations, e.g., bats can mobilize as many as forty joints during a
single wingbeat, with some joints reaching over one thousand degrees per second
in angular speed. Copying bats flight is a significant ordeal, however, very
rewarding. Aerial drones with morphing bodies similar to bats can be safer,
agile and energy-efficient owing to their articulated and soft wings. Current
design paradigms have failed to copy bat flight because they assume only
closed-loop feedback roles and ignore computational roles carried out by
morphology. To respond to the urgency, a design framework called Morphing via
Integrated Mechanical Intelligence and Control (MIMIC) is proposed. In this
paper, using the dynamic model of Northeastern University's Aerobat, which is
designed to test the effectiveness of the MIMIC framework, it will be shown
that computational structures and closed-loop feedback can be successfully used
to mimic bats stable flight apparatus.
