Riccardo Rasconi

The “USOCs Knowledge Integration and dissemination for Space Science Experimentation” (Ulisse) is a project (funded by EU and indicated by REA as example of successful FP7 project in the Space field) whose objective is data valorization around the ISS experiments. Each USOC (User Support and Operation Centres) is responsible for a particular on-board facility that is to be operated to perform scientific experiments and to generate the related scientific data. One of the main problems that the USOC engineers have to tackle in their daily activities is the synthesis and management of the experiment plans which originate from the requests of the ESA Principal Investigators (PI) and that will have to be approved by the Columbus European Planning Team (EPT) during a phase called Increment Planning Process, and eventually executed on board the scientific facility controlled by the USOC. This work presents the Planning and Scheduling Service (Pss), i.e., the specific service that has been ...

This paper presents a particular approach to take advantage of ambient intelligence technology. It describes an example of intelligent infrastructure in which artificial intelligence problem solving technology is tweaked to monitor human beings in need of constant attention (eg, elderly people alone at home). The ROBOCARE Domestic Environment integrates vision sensors with software technology to supervise daily activities of a person at home. This paper specifically describes the original use of scheduling technology to ...

This paper describes the results of the ROBOCARE, a project aimed at creating an integrated environment endowed with heterogeneous software and robotic agents for assisting an elderly person at home. Specifically, a proactive environment for continuous daily activity monitoring has been created in which an autonomous robot acts as the main interactor with the person. This paper describes how the

ABSTRACT This paper addresses the job shop scheduling problem with time lags and sequence-dependent setup times. This is an extension of the job shop scheduling problem with many applications in real production environments. We propose a scatter search algorithm which uses path relinking and tabu search in its core. We consider both feasible and unfeasible schedules in the execution, and we propose effective neighborhood structures with the objectives of reducing the makespan and regain feasibility. We also define new procedures for estimating the quality of the neighbors. We conducted an experimental study to compare the proposed algorithm with the state-of-the-art, in benchmarks both with and without setups. In this study, our algorithm has obtained very competitive results in a reduced run time.

ABSTRACT This paper presents recent results on applying robust state-of-the-art AI Planning and Scheduling (P&S) tech-niques to mobile space robotic domains. The major con-tribution of this paper is an enhanced version of the ESTA scheduling algorithm which is to capture all relevant as-pects of the robot activity scheduling problem in the space domain of interest. Furthermore, we provide an ex-ample of how the new solver can be used within a simple model-based autonomous control system for robust ac-tion scheduling and flexible reactive schedule execution for: (1) providing initial schedule solutions and (2) re-pairing invalidated schedules during execution because of unexpected external events.

ABSTRACT This paper presents recent results on applying advanced autonomous reasoning capabilities for a planetary rover concept for synthesizing complete command plans that involve a wide assortment of mission requirements. Our solution exploits AI scheduling techniques to manage complex temporal and resource constraints within an integrated power-aware decision-making strategy. The main contributions of this work are the following: (i) we propose a model of the world inspired by the Mars Sample Return (MSR) mission concept, a long-range planetary exploration scenario; (ii) we introduce a MSR-inspired scheduling problem called Power Aware Resource Constrained Mars Rover Scheduling (PARC-MRS), and we present an extension of a well-known constraint-based, resource-driven reasoner that returns rover activity plans as solutions of the PARC-MRS; (iii) we present a benchmark instance generator used to create reproducible PARC-MRS problem sets on the basis of the rover models' specifications contained within the ESA's 3DROV simulator; finally, (iv) we conduct an exhaustive experimentation to report the quality of the generated solutions according to both feasibility and makespan optimization criteria.

ABSTRACT The main result of the paper is the reduction of the RCPSP/max problem to a Disjunctive Temporal Problem that allows customization of specific properties within a backtracking search procedure for makespan optimization. In addition, a branching strategy is proposed able to deduce new constraints which explicitly represent infeasible or useless search paths. A new variable ordering heuristic (called clustering) is also used which provides a further boosting to the algorithm's effectiveness.

ULISSE is an EU project that aims at data valorization around the ISS experiments. The ULISSE software platform is endowed with a number of additional services to improve both data production and data analysis. This paper describes the Planning and Scheduling Service (PSS), a module developed to support functions of data production around the ISS activities and integrated in the ULISSE platform. In particular, the PSS is a software application developed within the Timeline Representation Framework and relies on a combination of different P&S algorithms in a loosely coupled way. Its current use to support Increment Planning activities for the Fluid Science Laboratory facility is shown and fully analyzed from design to application service delivery.