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The control of insect-sized flapping-wing micro air vehicles is attracting increasing interest. Solution of the problem requires construction of a controller that is physically small, extremely power efficient, and capable. In addition, process variation in the creation of very small wings and armatures as well as the potential for accumulating damage and wear over the course of a vehicle´s lifetime suggest that controllers be able to self-adapt to the specific and possibly changing nature of the vehicles in which they are embedded. Previous work with Evolvable Hardware Continuous Time Recurrent Neural Networks (CTRNNs) as applied to adaptive control of walking in legged robots suggests that CTRNNs may provide a suitable control solution for flapping-wing micro air vehicles. However, upon complete analysis, it can be seen that perceived similarities between the two problems are somewhat superficial, and that flapping-wing vehicle control requires its own study. This book constitutes the first of its kind attempts, to apply evolvable CTRNN devices to demonstrate feasibility flight controllers for a flapping-wing micro air vehicle.

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Dr. Sanjay Kumar Boddhu, works as a Researcher at Qbase (Metacarta). He evaluates, develops and designs technologies in the fields related to NLP, Evolutionary Computing, Human Centric Sensing, Computational Intelligence.He is also an invited advising researcher for research programs at Wright Brothers Institute´s ICC and Wright State University.

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