There is recent biological evidence that the pectoral fins of bluegill sunfish are innervated with nerves that respond to bending, and these fish contact obstacles with their fins. However, it is not known how fin-intrinsic sensing could be used to mediate propulsion and touch in engineered fins. The objective of this thesis is to understand the use of distributed sensing in robotic fins, inspired by bony fish fins, for the prediction of propulsive forces and for the discrimination between fluidic loading and contact loading during underwater touch. The research integrates engineering and biology and builds an understanding of fin-intrinsic sensing through study of swimming fish and robotic models of fish fins and sensors. Multiple studies identify which sensor types, sensor placement locations, and model conditions are best for predicting fin propulsive forces and for predicting the state of contact. Comparisons are made between linear and nonlinear Volterra-series convolution models to represent the mapping from sensory data to forces. Best practices for instrumentation and model selection are extracted for a broad range of swimming conditions on a complex, multi-DOF, flexible fin. This knowledge will guide the development of multi-functional systems to navigate and propel through complex, occluded, underwater environments and for sensing and responding to environmental perturbations and obstacles.Ph.D., Mechanical Engineering and Mechanics -- Drexel University, 201
