Loukas Petrou

TL;DR: The contribution of this work includes the definition of metrics for path planning benchmarks, actual benchmarks of the most common global path planning algorithms and an educated algorithm parameterization based on a global obstacle density coefficient.

TL;DR: The Bayesian Combined Predictor is presented, a probabilistically motivated predictor for time series prediction which produces a final prediction which is a weighted combination of the local predictions which can be interpreted as Bayesian posterior probabilities and computed online.

TL;DR: This paper uses Multi-Objective optimization in order to estimate, and subsequently, make an offer for its assignment, and provides a generic solution, independent of the domain, with an aim to better utilize resources such as time or energy.

TL;DR: In this article, a robotic system incorporating vision and force/torque sensing for handling flat textile materials is presented, where representative tasks have been selected which are further analyzed into simple operations.

TL;DR: In this article, an anaerobic digestion identification and control scheme, based on adaptive, on-line trained neural networks, is proposed. But the proposed control scheme is not suitable for the control of large-scale systems with complex nonlinear dynamics and difficult to measure or time varying parameters.