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Reliable navigation and localization systems are crucial for Autonomous Underwater Vehicles (AUVs). The limitations of electromagnetic signals underwater make the use of the Global Positioning System (GPS) impractical. As a result, real-time positioning often relies on expensive sensors like the Doppler Velocity Log (DVL) or acoustic ranging, integrated through sensor fusion techniques. This study investigates and compares three inverse dynamic models designed to estimate the velocity of AUVs using cost-effective Inertial Measurement Units (IMUs) and a model of thrust output based on Pulse Width Modulation (PWM) signals. These velocity estimates are then integrated with an Extended Kalman Filter (EKF) to determine the AUV’s state, and results are validated against ground truth data. Our findings demonstrate the feasibility and effectiveness of these models in providing a reliable and economical solution for low-cost AUV navigation, which is particularly interesting in swarm applications.

Modeling of soft robots is typically performed at the static level or at a second-order fully dynamic level. Controllers developed upon these models have several advantages and disadvantages. Static controllers, based on the kinematic relations tend to be the easiest to develop, but by sacrificing accuracy, efficiency and the natural dynamics. Controllers developed using second-order dynamic models tend to be computationally expensive, but allow optimal control. Here we propose that the dynamic model of a soft robot can be reduced to first-order dynamical equation owing to their high damping and low inertial properties, as typically observed in nature, with minimal loss in accuracy. This paper investigates the validity of this assumption and the advantages it provides to the modeling and control of soft robots. Our results demonstrate that this model approximation is a powerful tool for developing closed-loop task-space dynamic controllers for soft robots by simplifying the planning and sensory feedback process with minimal effects on the controller accuracy.

This paper entails the study of the pulsed-jet propulsion inspired by cephalopods in the frame of underwater bioinspired robotics. This propulsion routine involves a sequence of consecutive cycles of inflation and collapse of an elastic bladder, which, in the robotics artefact developed by the authors, is enabled by a cable-driven actuation of a deformable shell composed of rubber-like materials. In the present work an all-comprehensive formulation is derived by resorting to a coupled approach that comprises of a model of the structural dynamics of the cephalopod-like elastic bladder and a model of the pulsed-jet thrust production. The bladder, or mantle, is modelled by means of geometrically exact, axisymmetric, nonlinear shell theory, which yields an accurate estimation of the forces involved in driving the deformation of the structure in water. By coupling these results with those from a standard thrust model, the behaviour of the vehicle propelling itself in water is derived. The constitutive laws of the shell are also exploited as control laws with the scope of replicating the muscle activation routine observed in cephalopods. The model is employed to test various shapes, material properties and actuation routines of the mantle. The results are compared in terms of speed performance in order to identify suitable design guidelines. Altogether, the model is tested in more than 50 configurations, eventually providing useful insight for the development of more advanced vehicles and bringing evidence of its reliability in studying the dynamics of both man-made cephalopod-inspired robots and live specimens.