Ricerc@Sapienza

This paper presents two dynamic and distributed clustering algorithms for Wireless Sensor Networks (WSNs). Clustering approaches are used in WSNs to improve the network lifetime and scalability by balancing the workload among the clusters. Each cluster is managed by a cluster head (CH) node. The first algorithm requires the CH nodes to be mobile: by dynamically varying the CH node positions, the algorithm is proved to converge to a specific partition of the mission area, the generalised Voronoi tessellation, in which the loads of the CH nodes are balanced.

In this paper we propose an anytime planning/replanning algorithm aimed at generating motions allowing a humanoid to fulfill an assigned task that implicitly requires stepping. The algorithm interleaves planning and execution intervals: a previously planned whole-body motion is executed while simultaneously planning a new solution for the subsequent execution interval. At each planning interval, a specifically designed randomized local planner builds a tree in configuration-time space by concatenating successions of CoM movement primitives. Such a planner works in two stages.

A redundant robotic system must execute a task in a workspace populated by obstacles whose motion is unknown in advance. For this problem setting, we present a sensor-based planner that uses Model Predictive Control (MPC) to generate motion commands for the robot. We also propose a real-time implementation of the planner based on ACADO, an open source toolkit for solving general nonlinear MPC problems. The effectiveness of the proposed algorithm is shown through simulations and experiments carried out on a UR10 manipulator.

Purpose: The purpose of this paper is to investigate additive manufacturing (AM) phenomenon extending previous research results by studying in-depth the economic sustainability of AM technology and bringing out the contextual factors that drive its superior performances in comparison with conventional manufacturing, and justify its adoption in rapid prototyping (RP) from an economic point of view. Design/methodology/approach: Data have been collected through a worldwide survey. Respondents were from 105 companies adopting the technology from 23 countries worldwide.

This paper represents a first attempt toward an alternative way of computing reduction-based feedback à la Arstein for input-delayed systems. To this end, we first exhibit a new reduction state evolving as a new dynamics which is free of delays. Then, feedback design is carried out by enforcing passivity-based arguments in the reduction time-delay scenario. The case of strict-feedforward dynamics serves as a case study to discuss in details the computational advantages. A simulated exampled highlights performances.

In this work, the notion of reduction is introduced for discrete-time nonlinear input-delayed systems. The retarded dynamics is reduced to a new system which is free of delays and equivalent (in terms of stabilizability) to the original one. Different stabilizing strategies are proposed over the reduced model. Connections with existing predictor-based methods are discussed. The methodology is also worked out over particular classes of time-delay systems as sampled-data dynamics affected by an entire input delay.

In this paper, we consider the problem of disturbance decoupling for a class of non-minimum-phase nonlinear systems. Based on the notion of partially minimum phaseness, we shall characterize all actions of disturbances which can be decoupled via a static state feedback while preserving stability of the internal residual dynamics. The proposed methodology is then extended to the sampled-data framework via multi-rate design to cope with the rising of the so-called sampling zero dynamics intrinsically induced by classical single-rate sampling.

The paper deals with stabilization of feedforwardmultiple cascade dynamics under sampling. It is shown that u-average passivity concepts and Lyapunov methods can be profitably exploited to provide a systematic sampled-data design procedure. The proposed methodology recalls the continuous-time feedforwarding steps and can be applied under the same assumptions as those set over the continuous-time cascade dynamics. The final sampled feedback is carried out through a three steps procedure that involves iterative passivation and stabilization in the u-average sense.

The energy efficiency is the possibility and ability to carry out a production process consume with the involves of less energy and minor environmental impact. Life Cycle Assessment is one of the major tools involved in the economic, social and environmental evaluation. The aim of this work is the LCA application to an Italian company that provides to install a photovoltaic plant for the energy self-maintenance, in order to break down costs and environmental impacts. The photovoltaic business can be an interesting solution especially for companies which consume more energy during the day.