Daniele Nardi

TL;DR: In this paper, the Flourish research project aimed to develop an adaptable robotic solution for precision farming that combines the aerial survey capabilities of small autonomous unmanned aerial vehicles (UAVs) with targeted intervention performed by multipurpose unmanned ground vehicles (UGVs).

TL;DR: This paper addresses the representation and use of the knowledge that the system knows not to be possessed by the student, and points out several improvements that can be easily achieved by exploiting the features of a declarative approach.

TL;DR: In this paper , the authors proposed a Wavelet Recurrent Network (WRNN) for multidimensional time series prediction, which combines RNN and the Wavelet Transform into a unique neural network.

TL;DR: This paper designs the Dialogue Manager as a multi-objective Markov Decision Process, solving the optimisation problem through Reinforcement Learning, and provides a demonstration of the complete system on a real robot.

TL;DR: In this paper, the authors propose a multi-modal interaction framework that allows the robot to acquire knowledge about the environment where the robot operates from the user's indications provided by the user, and then the robot can ground complex referential expressions for motion commands and devise topological navigation plans to achieve the target locations.