Toward a general purpose software environment for timeline-based planning

Timeline-based Planning and Scheduling applications have been successfully deployed in various contexts. Often such applications use specific solving algorithms and cannot be easily applied for solving different kind of problems. Then, an open research issue for such planning modeling is the one of creating a software infrastructure with a controllable search engine. In this regard, this paper presents an attempt to synthesize such a software environment. The Extensible Planning and Scheduling Library (EPSL) evolves from the Timeline Representation Framework (APSI-TRF), a software environment supported by the European Space Agency. Goal of EPSL is to obtain a software architecture having the flexibility to focus on specific problem solving aspects. The paper is an initial report on this effort: it introduces the whole idea, then focuses on the definition of suitable heuristic functions, and presents experiments related to two domains generated by current applications

Optimal task and motion planning and execution for human-robot multi-agent systems in dynamic environments

Combining symbolic and geometric reasoning in multi-agent systems is a challenging task that involves planning, scheduling, and synchronization problems. Existing works overlooked the variability of task duration and geometric feasibility that is intrinsic to these systems because of the interaction between agents and the environment. We propose a combined task and motion planning approach to optimize sequencing, assignment, and execution of tasks under temporal and spatial variability. The framework relies on decoupling tasks and actions, where an action is one possible geometric realization of a symbolic task. At the task level, timeline-based planning deals with temporal constraints, duration variability, and synergic assignment of tasks. At the action level, online motion planning plans for the actual movements dealing with environmental changes. We demonstrate the approach effectiveness in a collaborative manufacturing scenario, in which a robotic arm and a human worker shall assemble a mosaic in the shortest time possible. Compared with existing works, our approach applies to a broader range of applications and reduces the execution time of the process.Comment: 12 pages, 6 figures, accepted for publication on IEEE Transactions on Cybernetics in March 202

AI and robotics to help older adults: Revisiting projects in search of lessons learned

Abstract This article is a retrospective overview of work performed in the domain of Active Assisted Living over a span of almost 18 years. The authors have been creating and refining artificial intelligence (AI) and robotics solutions to support older adults in maintaining their independence and improving their quality of life. The goal of this article is to identify strong features and general lessons learned from those experiences and conceive guidelines and new research directions for future deployment, also relying on an analysis of similar research efforts. The work considers key points that have contributed to increase the success of the innovative solutions grounding them on known technology acceptance models. The analysis is presented with a threefold perspective: A Technological vision illustrates the characteristics of the support systems to operate in a real environment with continuity, robustness, and safety; a Socio-Health perspective highlights the role of experts in the socio-assistance domain to provide contextualized and personalized help based on actual people's needs; finally, a Human dimension takes into account the personal aspects that influence the interaction with technology in the long term experience. The article promotes the crucial role of AI and robotics in ensuring intelligent and situated assistive behaviours. Finally, considering that the produced solutions are socio-technical systems, the article suggests a transdisciplinary approach in which different relevant disciplines merge together to have a complete, coordinated, and more informed vision of the problem

Planning and execution with robot trajectory generation in industrial human-robot collaboration

The co-presence of a robot and a human sharing some activities in an industrial setting constitutes a challenging scenario for control solutions, requiring highly flexible controllers to preserve productivity and enforce human safety. Standard methods are not suitable given the lack of methodologies able to evaluate robot execution time variability, caused by the necessity to continuously modify/adapt robot motions to grant human safety. This paper presents a novel dynamic planning system for Human-Robot Collaboration (HRC) which leverages an offline motion planning technique and deploys planning and execution features dealing with temporal uncertainty and kinematics both at planning and execution time. The proposed system is deployed in a manufacturing case study for controlling a working cell in which a robot and a human collaborate to achieve a shared production goal. The approach has been shown to be feasible and effective in a real case study

Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019

One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [...] This grand challenge extends this further by asking if we can create a knowledge graph of "everything" ranging from common sense concepts to location based entities. This knowledge graph should be "open to the public" in a FAIR manner democratizing this mass amount of knowledge." Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides a unique testbed for experimenting and evaluating research hypotheses on open and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing evolution and long term preservation. We want to investigate this problem, that is to understand what preserving and supporting the evolution of KGs means and how these problems can be addressed. Clearly, the problem can be approached from different perspectives and may require the development of different approaches, including new theories, ontologies, metrics, strategies, procedures, etc. This document reports a collaborative effort performed by 9 teams of students, each guided by a senior researcher as their mentor, attending the International Semantic Web Research School (ISWS 2019). Each team provides a different perspective to the problem of knowledge graph evolution substantiated by a set of research questions as the main subject of their investigation. In addition, they provide their working definition for KG preservation and evolution

A Formal Account of Planning with Flexible Timelines

Planning for real world problems with explicit temporal constraints is a challenging problem. Among several approaches, the use of flexible timelines in Planning and Scheduling (P&S) has demonstrated to be successful in a number of concrete applications, such as, for instance, autonomous space systems. A flexible timeline describes an envelope of possible solutions which can be exploited by an executive system for robust on-line execution. A remarkable research effort has been dedicated to design, build and deploy software environments, like EUROPA, ASPEN, and APSI-TRF, for the synthesis of timeline-based P&S applications. Several attempts have also been made to characterize the concept of timelines. Nevertheless, a formal characterization of flexible timelines and plans is still missing. This paper presents a formal account of flexible timelines aiming at providing a general semantics for related planning concepts such as domains, goals, problems, constraints and flexible plans. Some basic properties of the defined concepts are also stated and proved. A simple running example inspired by a real world planning domain is exploited to illustrate the proposed formal notions. Finally, a planning tool, called Extensible Planning and Scheduling Library (EPSL), is briefly presented, which is able to generate flexible plans that are compliant with the given semantics

Adaptive Robot Navigation through Integrated Task and Motion Planning

Robots acting in real-world environments usually interact with humans. Interactions may occur at different levels of abstraction (e.g., process, task, physical), entailing different research challenges (e.g., task allocation, human-robot joint actions, robot navigation). When acting in social situations, robots should recognize the context and behave in different manners, so as to act and interact in a correct and acceptable way. We propose the integration of task and motion planning to contextualize robot behaviors for social navigation. The main idea is to leverage the contextual knowledge of a deliberative task planner to dynamically adapt the navigation behaviors of a robot and enhance humanrobot interaction. More specifically, we propose a holistic model of tasks and human features and a mapping from task-level knowledge to motion-level knowledge to constrain the generation of robot trajectories. The proposed framework is tested in simulation for some commonly occurring scenarios in a hospital