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This paper presents a dynamic model for a class of robotic fish propelled by a tail with a flexible fin. The robot is comprised of a rigid frontal link acting as a body and a rear link serving as the tail. The tail includes a rigid component, hinged to the body through a servomotor, which is connected to a compliant caudal fin whose underwater vibration induces the propulsion. The robot’s body dynamics is modeled using Kirchhoff’s equations of motion of bodies in quiescent fluids, while its tail motion is described with Euler-Bernoulli beam theory, accounting for the effect of the encompassing fluid through the Morison equation. Simulation data of the model is compared with experimental data. Applications of the model include simulation, prediction, design optimization, and control.

In this paper, we introduce a novel optimization framework for a station-to-door mobility-on-demand system that aims at ensuring an efficient transportation service for the daily mobility of passengers in densely populated urban areas. We propose a mixed integer linear programming approach that maximizes both the customers' satisfaction and the provider's revenues, keeping at the same time the number of vehicles in each station within given bounds towards the improvement of system balancing. The proposed customer-oriented approach aims at meeting as many customer requests as possible, while maximizing the provider revenues and reducing the customers' impatience, thus increasing their satisfaction. This implies, in turn, a better reputation for the service provider. The performance of the proposed approach is assessed through an extensive Monte Carlo simulation campaign. In particular, through the analysis of different performance indices, we compare the optimal solution of the proposed approach with the optimal solution achieved by a previously presented approach based on the Profitable Tour Problem.