Fish use coordinated motions of multiple fins and their body to swim and maneuver underwater with more agility than contemporary unmanned underwater vehicles (UUVs). The location, utilization and kinematics of fins vary for different locomotory tasks and fish species. The relative position and timing (phase) of fins affects how the downstream fins interact with the wake shed by the upstream fins and body, and change the magnitude and temporal profile of the net force vector. A multifin biorobotic experimental platform and a two-dimensional computational fluid dynamic simulation were used to understand how the propulsive forces produced by multiple fins were affected by the phase and geometric relationships between them. This investigation has revealed that forces produced by interacting fins are very different from the vector sum of forces from combinations of noninteracting fins, and that manipulating the phase and location of multiple interacting fins greatly affect the magnitude and shape of the produced propulsive forces. The changes in net forces are due, in large part, to time-varying wakes from dorsal and anal fins altering the flow experienced by the downstream body and caudal fin. These findings represent a potentially powerful means of manipulating the swimming forces produced by multifinned robotic systems.

The remarkable swimming abilities of bony fish are the result of multiple interacting subsystems, each tuned to perform certain roles. These subsystems, which include the statically unstable body, multiple highly actuated fins, oscillatory neural controllers, and distributed senses, are not often studied as mutually dependent systems. This research program is developing biorobotic models of these systems and integrating the systems into a biorobotic fish so that interdependencies can be explored during free swimming. The robot body was derived from a bluegill sunfish, and has a tunable mass distribution and a mixture of rigid and flexible sections so that dynamical characteristics of the fish body can be explored. Five highly deformable fins have structural properties scaled to those of biological fins and can create gait patterns for steady swimming and maneuvers. A first generation artificial CPG has been programmed for each fin on a network of five low power microcontrollers. Finally, a dedicated biorobotic pectoral fin has been developed and instrumented with distributed sensory systems so relevant physical (e.g., fin curvature) and hydrodynamic (e.g., pressure) data can be identified and used to predict fin force for closed loop control.

Bioinspired robotic designs have proven to be effective models for autonomous vehicles as well as important research tools in comparative biomechanics. Here we review the process by which we investigated the functional morphology and biomechanics of fish fins using live fish experiments and computational modeling; created and validated independent fins with regard to biological properties like stiffness, kinematics, and fluid dynamics; and constructed an autonomous underwater vehicle with a sensory feedback system to respond to perturbations.

The remarkable swimming abilities of bony fish are the result of multiple interacting subsystems, each tuned to perform certain roles. These subsystems, which include the statically unstable body, multiple highly actuated fins, oscillatory neural controllers, and distributed senses, are not often studied as mutually dependent systems. This research program is developing biorobotic models of these systems and integrating the systems into a biorobotic fish so that interdependencies can be explored during free swimming. The robot body was derived from a bluegill sunfish, and has a tunable mass distribution and a mixture of rigid and flexible sections so that dynamical characteristics of the fish body can be explored. Five highly deformable fins have structural properties scaled to those of biological fins and can create gait patterns for steady swimming and maneuvers. A first generation artificial CPG has been programmed for each fin on a network of five low power microcontrollers. Finally, a dedicated biorobotic pectoral fin has been developed and instrumented with distributed sensory systems so relevant physical (e.g., fin curvature) and hydrodynamic (e.g., pressure) data can be identified and used to predict fin force for closed loop control.