Planning Technologies for the Web Environment: Perspectives and Research Issues

This work will explore and motivate perspectives and research issues related with the applications of automated planning technologies in order to support innovative web applications. The target for the technology transfer, i.e. the web, and, in a broader sense, the new Information Technologies (IT) is one of the most changing, evolving and hottest areas of current computer science. Nevertheless many sub-area in this field could have potential benefits from Planning and Scheduling (P&S) technologies, and, in some cases, technology transfer has already started. This paper will consider and explore a set of topics, guidelines and objectives in order to implement the technology transfer a new challenges, requirements and research issues for planning which emerge from the web and IT industry. Sample scenarios will be depicted to clarify the potential applications and limits of current planning technology. Finally we will point out some new P&S research challenge issues which are required to meet more advanced applicative goals

Interactive Execution Monitoring of Agent Teams

There is an increasing need for automated support for humans monitoring the activity of distributed teams of cooperating agents, both human and machine. We characterize the domain-independent challenges posed by this problem, and describe how properties of domains influence the challenges and their solutions. We will concentrate on dynamic, data-rich domains where humans are ultimately responsible for team behavior. Thus, the automated aid should interactively support effective and timely decision making by the human. We present a domain-independent categorization of the types of alerts a plan-based monitoring system might issue to a user, where each type generally requires different monitoring techniques. We describe a monitoring framework for integrating many domain-specific and task-specific monitoring techniques and then using the concept of value of an alert to avoid operator overload. We use this framework to describe an execution monitoring approach we have used to implement Execution Assistants (EAs) in two different dynamic, data-rich, real-world domains to assist a human in monitoring team behavior. One domain (Army small unit operations) has hundreds of mobile, geographically distributed agents, a combination of humans, robots, and vehicles. The other domain (teams of unmanned ground and air vehicles) has a handful of cooperating robots. Both domains involve unpredictable adversaries in the vicinity. Our approach customizes monitoring behavior for each specific task, plan, and situation, as well as for user preferences. Our EAs alert the human controller when reported events threaten plan execution or physically threaten team members. Alerts were generated in a timely manner without inundating the user with too many alerts (less than 10 percent of alerts are unwanted, as judged by domain experts)

Designing Distributed, Component-Based Systems for Industrial Robotic Applications

none3noneM. Amoretti; S. Caselli; M. ReggianiM., Amoretti; S., Caselli; Reggiani, Monic

An Adaptive Approach for Planning in Dynamic Environments

Planning in a dynamic environment is a complex task that requires several issues to be investigated in order to manage the associated search complexity. In this paper, an adaptive behavior that integrates planning with learning is presented. The former is performed adopting a hierarchical approach, interleaved with execution. The latter, devised to identify new abstract operators, adopts a chunking technique on successful plans. Integration between planning and learning is also promoted by an agent architecture explicitly designed for supporting abstraction

Towards formal models and languages for verifiable Multi-Robot Systems

Incorrect operations of a Multi-Robot System (MRS) may not only lead to unsatisfactory results, but can also cause economic losses and threats to safety. These threats may not always be apparent, since they may arise as unforeseen consequences of the interactions between elements of the system. This call for tools and techniques that can help in providing guarantees about MRSs behaviour. We think that, whenever possible, these guarantees should be backed up by formal proofs to complement traditional approaches based on testing and simulation. We believe that tailored linguistic support to specify MRSs is a major step towards this goal. In particular, reducing the gap between typical features of an MRS and the level of abstraction of the linguistic primitives would simplify both the specification of these systems and the verification of their properties. In this work, we review different agent-oriented languages and their features; we then consider a selection of case studies of interest and implement them useing the surveyed languages. We also evaluate and compare effectiveness of the proposed solution, considering, in particular, easiness of expressing non-trivial behaviour.Comment: Changed formattin

Unified Behavior Framework for Reactive Robot Control in Real-Time Systems

Endeavors in mobile robotics focus on developing autonomous vehicles that operate in dynamic and uncertain environments. By reducing the need for human-in- the-loop control, unmanned vehicles are utilized to achieve tasks considered dull or dangerous by humans. Because unexpected latency can adversely affect the quality of an autonomous system\u27s operations, which in turn can affect lives and property in the real-world, their ability to detect and handle external events is paramount to providing safe and dependable operation. Behavior-based systems form the basis of autonomous control for many robots. This thesis presents the unified behavior framework, a new and novel approach which incorporates the critical ideas and concepts of the existing reactive controllers in an effort to simplify development without locking the system developer into using any single behavior system. The modular design of the framework is based on modern software engineering principles and only specifies a functional interface for components, leaving the implementation details to the developers. In addition to its use of industry standard techniques in the design of reactive controllers, the unified behavior framework guarantees the responsiveness of routines that are critical to the vehicle\u27s safe operation by allowing individual behaviors to be scheduled by a real-time process controller. The experiments in this thesis demonstrate the ability of the framework to: 1) interchange behavioral components during execution to generate various global behavior attributes; 2) apply genetic programming techniques to automate the discovery of effective structures for a domain that are up to 122 percent better than those crafted by an expert; and 3) leverage real-time scheduling technologies to guarantee the responsiveness of time critical routines regardless of the system\u27s computational load

Modeling Human-Robot-Interaction based on generic Interaction Patterns

Peltason J. Modeling Human-Robot-Interaction based on generic Interaction Patterns. Bielefeld: Bielefeld University; 2014

Modular and Safe Event-Driven Programming

Asynchronous event-driven systems are ubiquitous across domains such as device drivers, distributed systems, and robotics. These systems are notoriously hard to get right as the programmer needs to reason about numerous control paths resulting from the complex interleaving of events (or messages) and failures. Unsurprisingly, it is easy to introduce subtle errors while attempting to fill in gaps between high-level system specifications and their concrete implementations.This dissertation proposes new methods for programming safe event-driven asynchronous systems.In the first part of the thesis, we present ModP, a modular programming framework for compositional programming and testing of event-driven asynchronous systems.The ModP module system supports a novel theory of compositional refinement for assume-guarantee reasoning of dynamic event-driven asynchronous systems. We build a complex distributed systems software stack using ModP.Our results demonstrate that compositional reasoning can help scale model-checking (both explicit and symbolic) to large distributed systems.ModP is transforming the way asynchronous software is built at Microsoft and Amazon Web Services (AWS). Microsoft uses ModP for implementing safe device drivers and other software in the Windows kernel.AWS uses ModP for compositional model checking of complex distributed systems. While ModP simplifies analysis of such systems, the state space of industrial-scale systems remains extremely large.In the second part of this thesis, we present scalable verification and systematic testing approaches to further mitigate this state-space explosion problem.First, we introduce the concept of a delaying explorer to perform prioritized exploration of the behaviors of an asynchronous reactive program. A delaying explorer stratifies the search space using a custom strategy (tailored towards finding bugs faster), and a delay operation that allows deviation from that strategy. We show that prioritized search with a delaying explorer performs significantly better than existing approaches for finding bugs in asynchronous programs.Next, we consider the challenge of verifying time-synchronized systems; these are almost-synchronous systems as they are neither completely asynchronous nor synchronous.We introduce approximate synchrony, a sound and tunable abstraction for verification of almost-synchronous systems. We show how approximate synchrony can be used for verification of both time-synchronization protocols and applications running on top of them.Moreover, we show how approximate synchrony also provides a useful strategy to guide state-space exploration during model-checking.Using approximate synchrony and implementing it as a delaying explorer, we were able to verify the correctness of the IEEE 1588 distributed time-synchronization protocol and, in the process, uncovered a bug in the protocol that was well appreciated by the standards committee.In the final part of this thesis, we consider the challenge of programming a special class of event-driven asynchronous systems -- safe autonomous robotics systems.Our approach towards achieving assured autonomy for robotics systems consists of two parts: (1) a high-level programming language for implementing and validating the reactive robotics software stack; and (2) an integrated runtime assurance system to ensure that the assumptions used during design-time validation of the high-level software hold at runtime.Combining high-level programming language and model-checking with runtime assurance helps us bridge the gap between design-time software validation that makes assumptions about the untrusted components (e.g., low-level controllers), and the physical world, and the actual execution of the software on a real robotic platform in the physical world. We implemented our approach as DRONA, a programming framework for building safe robotics systems.We used DRONA for building a distributed mobile robotics system and deployed it on real drone platforms. Our results demonstrate that DRONA (with the runtime-assurance capabilities) enables programmers to build an autonomous robotics software stack with formal safety guarantees.To summarize, this thesis contributes new theory and tools to the areas of programming languages, verification, systematic testing, and runtime assurance for programming safe asynchronous event-driven across the domains of fault-tolerant distributed systems and safe autonomous robotics systems

Characterizing and evaluating autonomous controllers

Premio Extraordinario de Doctorado de la UAH en el año académico 2016-2017La autonomía en robótica por medio de técnicas de Inteligencia Artificial, particularmente mediante el empleo sistemas de Planning & Scheduling (P&S), presenta un amplio campo de investigación con gran interés en aplicaciones como la robótica de exploración para entornos hostiles o difícilmente accesibles para los humanos. Sin embargo, las pruebas experimentales realizadas en los artículos de divulgación científica sobre controladores autónomos generalmente no están correctamente realizadas, ya que se carece de una metodología de estudio común. En este sentido se hace complicado comparar los nuevos sistemas con los trabajos previos, práctica habitual en otras disciplinas. Por ello, en esta tesis se propone un entorno de trabajo llamado On-Ground Autonomy Test Environment (OGATE) para permitir la evaluación de controladores autónomos. Este desarrollo consta de una metodología para estructurar la fase experimental, así como de un conjunto de métricas independientes tanto del dominio como del campo de aplicación del sistema robótico. La unión de estos elementos, mediante un software que automatiza el proceso experimental, permite obtener evaluaciones reproducibles y objetivas sobre los controladores autónomos bajo estudio. Para demostrar la efectividad del entorno de trabajo, se han utilizado dos controladores autónomos basados en diferentes paradigmas para P&S. Primero se ha utilizado el Goal Oriented Autonomous Controller (GOAC), desarrollado bajo contrato de la Agencia Espacial Europea. Segundo, durante esta tesis se ha implementado la Model-Based Architecture (MoBAr). MoBAr está diseñado con el objetivo de probar diferentes planificadores basados en el Planning Domain Definition Language (PDDL) para conseguir autonomía a bordo. En este sentido, en la tesis también se introduce un nuevo planificador llamado Unified Path Planning and Task Planning Architecture (UP2TA). Dicho sistema integra un planificador general basado en PDDL y algoritmos de planificación de rutas con el objetivo de generar planes más seguros y eficientes para robots de exploración. Referente a la planificación de rutas, en la tesis se incluye la definición de dos nuevos algoritmos enfocados en la movilidad de los robots de exploración: S-Theta* y 3D Accurate Navigation Algorithm (3Dana). S-Theta* permite obtener rutas con un menor número de cambios de dirección que algoritmos previos, mientras que 3Dana genera rutas más seguras y restringidas en función de la pendiente del entorno, empleando para ello Modelos Digitales de Terreno (MDT) y mapas de costes trasversales. Partiendo de GOAC y MoBAr, se ha empleado OGATE para evaluar ambos controladores, siendo posible caracterizar aspectos relevantes de la integración entre Planning & Execution (P&E) difícilmente accesibles mediante otros enfoques. Además, los resultados obtenidos son objetivos y reproducibles, permitiendo realizar comparaciones entre controladores autónomos con diferentes tecnologías y/o paradigmas de P&S