This work aims at reviewing, analyzing and comparing a range of state-of-the-art
approaches to inertial parameter identification in the context of robotics. We introduce …

A robotic gras** simulator, called Graspit!, is presented as versatile tool for the gras**
community. The focus of the grasp analysis has been on force-closure grasps, which are …

In this article, we present a metaheuristic-based control framework, called beetle antennae
olfactory recurrent neural network, for simultaneous tracking control and obstacle avoidance …

With the wide application of industrial robots in the field of precision machining, reliability
analysis of positioning accuracy becomes increasingly important for industrial robots. Since …

There is growing need for software tools that can accurately simulate the complex dynamics
of modern robots. While a number of candidates exist, the field is fragmented. It is difficult to …

We reconsider randomized algorithms for the low-rank approximation of SPSD matrices
such as Laplacian and kernel matrices that arise in data analysis and machine learning …

Pressing demands of productivity and accuracy in today's robotic applications have
highlighted an urge to replace classical control strategies with their modern control …

Leveraging the elastic bodies of soft robots promises to enable the execution of dynamic
motions as well as compliant and safe interaction with an unstructured environment …

ViSP (Visual Servoing Platform), a fully functional modular architecture that allows fast
development of visual servoing applications, is described. The platform takes the form of a …

This thesis develops two Bayesian learning methods relying on Gaussian processes and a
rigorous statistical approach for evaluating such methods. In these experimental designs the …