An experimental validation of the polynomial curvature model: identification and optimal control of a soft underwater tentacle

The control possibilities for soft robots have long been hindered by the lack of accurate yet computationally treatable dynamic models of soft structures. Polynomial curvature models propose a solution to this quest for continuum slender structures. Nevertheless, the results produced with this class of models have been so far essentially...

Automated seismic acquisition geometry design for optimized illumination at the target: a linearized approach

In seismic exploration methods, imperfect spatial sampling at the surface causes a lack of illumination at the target in the subsurface. The hampered image quality at the target area of interest causes uncertainties in reservoir monitoring and production, which can have a substantial economic impact. Especially in the case of a complex...

Selecting Informative Data Samples for Model Learning Through Symbolic Regression

Continual model learning for nonlinear dynamic systems, such as autonomous robots, presents several challenges. First, it tends to be computationally expensive as the amount of data collected by the robot quickly grows in time. Second, the model accuracy is impaired when data from repetitive motions prevail in the training set and outweigh...

A State-Space Approach to Modelling DC Distribution Systems

Many modelling methods for the analysis of dc distribution grids only consider monopolar configurations and do not allow for mutual couplings to be taken into account. The modelling method presented in this paper aims to deal with both of these issues. A state-space approach was chosen for its flexibility and computational speed. The derived...