Federating Policy-Driven Autonomous Systems: Interaction Specification and Management Patterns

Ubiquitous systems and applications involve interactions between multiple autonomous entities—for example, robots in a mobile ad-hoc network collaborating to achieve a goal, communications between teams of emergency workers involved in disaster relief operations or interactions between patients’ and healthcare workers’ mobile devices. We have previously proposed the Self-Managed Cell (SMC) as an architectural pattern for managing autonomous ubiquitous systems that comprise both hardware and software components and that implement policy-based adaptation strategies. We have also shown how basic management interactions between autonomous SMCs can be realised through exchanges of notifications and policies, to effectively program management and context-aware adaptations. We present here how autonomous SMCs can be composed and federated into complex structures through the systematic composition of interaction patterns. By composing simpler abstractions as building blocks of more complex interactions it is possible to leverage commonalities across the structural, control and communication views to manage a broad variety of composite autonomous systems including peer-to-peer collaborations, federations and aggregations with varying degrees of devolution of control. Although the approach is more broadly applicable, we focus on systems where declarative policies are used to specify adaptation and on context-aware ubiquitous systems that present some degree of autonomy in the physical world, such as body sensor networks and autonomous vehicles. Finally, we present a formalisation of our model that allows a rigorous verification of the properties satisfied by the SMC interactions before policies are deployed in physical devices.     

面向运行的网络管理:基于政策的方法

基于政策的网络管理是提高大规模异构网络管理的自动化程度和网管系统的自适应能力的有效方法，但目前基于政策的网络管理由于政策描述方法和通信机制等原因．往往要求被管系统先进行这样或那样的升级．才能实施相应的管理．该文描述了一种与被管系统无关的、基于EBNF的政策描述语言，并提出了一个实用的管理框架，采用标准的SQL访问接口和事件驱动机制实现系统内各模块之间的通信；利用Tcl／tk／expect交互式脚本语言实现网管系统和被管设备之间的通信．政策描述语言能够描述各类抽象管理任务．所采用的通信机制不需要被管系统支持新的管理协议．因此可以在无需时现行网络作任何改动或升级的情况下实施基于政策的网络管理．     

A Generic Framework for Distributed Multirobot Cooperation

DEMiR-CF is a generic framework designed for a multirobot team to efficiently allocate tasks among themselves and achieve an overall mission. In the design of DEMiR-CF, the following issues were particularly investigated as the design criteria: efficient and realistic representation of missions, efficient allocation of tasks to cooperatively achieve a global goal, maintenance of the system coherence and consistency by the team members, detection of the contingencies and recover from various failures that may arise during runtime, efficient reallocation of tasks (if necessary) and reorganization of team members (if necessary). DEMiR-CF is designed to address different types of missions from the simplest to more complex ones, including missions with interrelated tasks and multi-resource (robot) requirements. Efficiency of the framework is validated through experiments in three different types of domains.     

A distributed architecture for supervision of autonomous multi-robot missions

Realizing long-term autonomous missions involving teams of heterogeneous robots is a challenge. It requires mechanisms to make robots react to disturbances or failures that will arise during the mission, while trying to successfully achieve the mission in cooperation. This paper presents HiDDeN, a distributed deliberative architecture that manages the execution of a hierarchical plan. This plan has initially been computed offline, ensuring some military operational constraints of the mission. Each robot’s supervisor then executes its own part of the plan, and reacts to failures using a hierarchical repair approach. This hierarchical repair has been designed with the sake of ensuring operational constraints, while reducing the need of communication between robots, as communication may be intermittent or even nonexistent when the robots operate in completely separate environments. HiDDeN’s robustness and scalability is evaluated with simulations. Experiments with an autonomous helicopter and an autonomous underwater vehicle have been realized and are presented as the defining point of our contribution.     

Coordination and Longevity in Multi-Robot Teams Involving Miniature Robots

Marsupial robot teams offer the ability to augment or replace human-based responses to hazardous scenarios such as search-and-rescue missions or monitoring toxic environments. Coordination and longevity of the members of the marsupial robotic team can quickly become burdensome as the scope of the scenario changes. To facilitate large scale operations, robotic teams must be able to function continuously with limited to no human intervention for scenarios which may not have a pre-determined length at onset. An end-to-end design and implementation of a novel marsupial system where a multi-level hierarchy allows larger robots to transport, deploy, coordinate, recover, and resupply large numbers of smaller deployable systems is outlined. The design and implementation of hardware systems for performing these actions is discussed. In addition, the algorithms which coordinate the team members are presented. Simulation illustrating the scalability of the approach is presented including experiments illustrating a light-weight vision-based autonomous docking capability.     

Design and validation of a light inference system to support embedded context reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.     

Dynamics of Innovation: Understanding and Influencing Communication Behaviours

Studies of communication patterns in technical teams have confirmed the importance of three roles (critic, erudite and idea generator) identified in earlier Russian work. Interpersonal needs and innovation-adaptation style preferences were also examined. The results demonstrate that the roles are taken up by team members with differing interpersonal needs and innovation-adaptation biases. The authors suggest that greater attention to such factors will assist in the design and management of more effective scientific teams, and describe an easy-to-apply survey-feedback method for facilitating team learning and development.     

Knowledge-based multimodal information fusion for role recognition and situation assessment by using mobile robot

Decision-making is the key for autonomous systems to achieve real intelligence and autonomy. This paper presents an integrated probabilistic decision framework for a robot to infer roles that humans fulfill in specific missions. The framework also enables the assessment of the situation and necessity of interaction with the person fulfilling the target role. The target role is the person who is distinctive in movement or holds a mission-critical object, where the object is pre-specified in the corresponding mission. The proposed framework associates prior knowledge with spatial relationships between the humans and objects as well as with their temporal changes. Distance-Based Inference (DBI) and Knowledge-Based Inference (KBI) support recognition of human roles. DBI deduces the role based on the relative distance between humans and the specified objects. KBI focuses on human actions and objects existence. The role is estimated using weighted fusion scheme based on the information entropy. The situation is assessed by analyzing the action of the person fulfilling the target role and relative position of this person to the mission-related entities, where the entity is something that has a particular function in the corresponding mission. This assessment determines the robot decision on what actions it should take. A series of experiments has proofed that the proposed framework provides a reasonable assessment of the situation. Moreover, it outperforms other approaches on accuracy, efficiency, and robustness.     

Autonomous UAV path planning and estimation

Unmanned aerial vehicles (UAVs) have shown promise in recent years for autonomous sensing. UAVs systems have been proposed for a wide range of applications such as mapping, surveillance, search, and tracking operations. The recent availability of low-cost UAVs suggests the use of teams of vehicles to perform sensing tasks. To leverage the capabilities of a team of vehicles, efficient methods of decentralized sensing and cooperative path planning are necessary. The goal of this work is to examine practical control strategies for a team of fixed-wing vehicles performing cooperative sensing. We seek to develop decentralized, autonomous control strategies that can account for a wide variety of sensing missions. Sensing goals are posed from an information theoretic standpoint to design strategies that explicitly minimize uncertainty. This work proposes a tightly coupled approach, in which sensor models and estimation objectives are used online for path planning.     

Local strategy learning in networked multi-agent team formation

Networked multi-agent systems are comprised of many autonomous yet interdependent agents situated in a virtual social network. Two examples of such systems are supply chain networks and sensor networks. A common challenge in many networked multi-agent systems is decentralized team formation among the spatially and logically extended agents. Even in cooperative multi-agent systems, efficient team formation is made difficult by the limited local information available to the individual agents. We present a model of distributed multi-agent team formation in networked multi-agent systems, describe a policy learning framework for joining teams based on local information, and give empirical results on improving team formation performance. In particular, we show that local policy learning from limited information leads to a significant increase in organizational team formation performance compared to a random policy.     

Simulation and control of distributed robot search teams

This article describes the simulation of distributed autonomous robots for search and rescue operations. The simulation system is utilized to perform experiments with various control strategies for the robot team and team organizations, evaluating the comparative performance of the strategies and organizations. The objective of the robot team is to, once deployed in an environment (floor-plan) with multiple rooms, cover as many rooms as possible. The simulated robots are capable of navigation through the environment, and can communicate using simple messages. The simulator maintains the world, provides each robot with sensory information, and carries out the actions of the robots. The simulator keeps track of the rooms visited by robots and the elapsed time, in order to evaluate the performance of the robot teams. The robot teams are composed of homogenous robots, i.e., identical control strategies are used to generate the behavior of each robot in the team. The ability to deploy autonomous robots, as opposed to humans, in hazardous search and rescue missions could provide immeasurable benefits.     

Modeling NASA swarm-based systems: using agent-oriented software engineering and formal methods

The need to collect new data and perform new science is causing the complexity of NASA missions to continually increase. This complexity needs to be controlled via new technological advancements and balanced with a reduction in mission and operation costs. Planned and hypothesized missions involve self-management, biological-inspiration based on swarms, and autonomous operation as a means of achieving these goals. We consider a tailored software engineering approach to developing such systems based on agent-oriented software engineering and formal methods. We report on advances in modeling, implementing, and testing NASA swarm-based concept missions.     

Naval Mine Countermeasure Missions

Undersea operations using autonomous underwater vehicles (AUVs) provide a different and in some ways a more challenging problem than tasks for unmanned aerial vehicles and unmanned ground vehicles. In particular, in undersea operations, communication windows are restricted, and bandwidth is limited. Consequently, coordination among agents is correspondingly more difficult. In traditional approaches, a central planner initially assigns subtasks to a set of AUVs to achieve the team goal. However, those initial task assignments may become inefficient during real-time execution because of the real-world issues such as failures. Therefore, initial task allocations are usually subject to change if efficiency is a high concern. Reallocations are needed and should be performed in a distributed manner. To provide such flexibility, we propose a distributed auction-based cooperation framework, distributed and efficient multirobot-cooperation framework (DEMiR-CF), which is an online dynamic task allocation (reallocation) system that aims to achieve a team goal while using resources effectively. DEMiR-CF, with integrated task scheduling and execution capabilities, can also respond to and recover from real-time contingencies such as communication failures, delays, range limitations, and robot failures.     

A conceptual framework to study the role of communication through social software for coordination in globally-distributed software teams

BackgroundIn Global Software Development (GSD) the lack of face-to-face communication is a major challenge and effective computer-mediated practices are necessary to mitigate the effect of physical distance. Communication through Social Software (SoSo) supports team coordination, helping to deal with geographical distance; however, in Software Engineering literature, there is a lack of suitable theoretical concepts to analyze and describe everyday practices of globally-distributed software development teams and to study the role of communication through SoSo.ObjectiveThe paper proposes a theoretical framework for analyzing how communicative and coordinative practices are constituted and maintained in globally-distributed teams.MethodThe framework is based on the concepts of communicative genres and coordination mechanisms; it is motivated and explicated through examples from two qualitative empirical cases.ResultsCoordination mechanisms and communicative genres mutually support each other. In particular, communication through SoSo supports team members in establishing, developing and maintaining social protocols within the distributed team. Software Engineering tools and methods provide templates for coordination mechanism that need to be adapted and adopted in order to support the project at hand. SoSo serves as a medium for the necessary metawork. The theoretical framework proposed is used to describe both the practices in an established industrial project and the establishing of practices in three student teams. The framework allows explaining the heterogeneity of practices observed.ConclusionsThis paper presents a conceptual framework to study the role of communication through SoSo for coordination in GSD. The usefulness of the framework is supported by empirical findings on the role of SoSo. The theoretical framework can be beneficial for future research that aims to analyze and describe not only the role of SoSo, but also how communicative and coordinative practices can be established and maintained in GSD teams.     

Cooperative research in underwater robot mission-level programming methodologies

Programming autonomous vehicles to accomplish complex missions is a complicated task for which the development of control architectures is of prime importance. The goal of this paper is to describe the accomplishments of both French and American teams within a cooperative research program focused on the development of high-level control of semi-autonomous underwater vehicles. In particular, two different mission-programming methodologies are examined in the context of the requirements of a generic, reactive and complex underwater mission. The French team uses a combination of the ESTEREL synchronous programming language and the PIRRAT real-time control library to implement a methodology derived from the ORCCAD programming system. The approach taken by the American team builds a trilevel hybrid architecture using the CONTROLSHELL real-time software development environment. The details of each methodology are highlighted through the presentation of the high-level programs designed by each team using their approach to control an underwater robot to perform a multiphased underwater mission. The utility of both programming methodologies was verified through the successful completion of those missions in experimental demonstrations by the French VORTEX and American OTTER autonomous underwater vehicles.     

The Entrapment/Escorting Mission

The problem of escorting a moving target with a team of mobile robots was solved in this article by resorting to a formation control algorithm that can be cast in the framework of the NSB control approach. The overall mission, therefore, is decomposed into properly defined elementary tasks that are hierarchically arranged, so that the higher-priority tasks are not influenced by the lower-priority ones. The validity of the proposed approach has been proved by both simulation case studies and experimental results with a team of six Khepera II mobile robots. Stability analysis concerning effective conditions needed to verify that the behaviors of specific missions are properly defined and merged is under investigation. Future improvements might regard decentralization of the algorithm, consideration of the vehicles' nonholonomicity in the definition of the task functions, and the introduction of a piecewise-constant constraint for the linear velocity to allow application of the method to teams of cruise vehicles (e.g., a fleet of vessels or a flight of planes).     

A Hybrid Framework for Mobile Robot Localization: Formulation Using Switching State-Space Models

In this paper we address one of the most important issues for autonomous mobile robots, namely their ability to localize themselves safely and reliably within their environments. We propose a probabilistic framework for modelling the robot's state and sensory information based on a Switching State-Space Model. The proposed framework generalizes two of the most successful probabilistic model families currently used for this purpose: the Kalman filter Linear models and the Hidden Markov Models. The proposed model combines the advantages of both models, relaxing at the same time inherent assumptions made individually in each of these existing models.     

Theoretical foundations of planning and navigation for autonomous robots

In this article, theoretical foundations of planning and navigation systems and processes are outlined in a form applicable for autonomous robotics. the core of the theory is based upon methods developed in the team theory of decentralized stochastic control. A class of autonomous control systems is defined, and a problem of information representation is addressed for this class. A phenomenon of nesting is determined to be a key element for arranging design and control procedures for systems of intelligent control. A concept of hierarchical nested knowledge-based controller is employed in this article which enables optimum control using nested dynamic programming. an application of this concept is unfolded for a system of knowledge-based control of an autonomous mobile robot.     

A system for self-diagnosis of an autonomous mobile robot using an internal state sensory system: fault detection and coping with the internal condition

Considering that intelligent robotic systems work in a real environment, it is important that they themselves have the ability to determine their own internal conditions. Therefore, we consider it necessary to pay some attention to the diagnosis of such intelligent systems and to construct a system for the self-diagnosis of an autonomous mobile robot. Autonomous mobile systems must have a self-contained diagnostic system and therefore there are restrictions to building such a system on a mobile robot. In this paper, we describe an internal state sensory system and a method for diagnosing conditions in an autonomous mobile robot. The prototype of our internal sensory system consists of voltage sensors, current sensors and encoders. We show experimental results of the diagnosis using an omnidirectional mobile robot and the developed system. Also, we propose a method that is able to cope with the internal condition using internal sensory information. We focus on the functional units in a single robot system and also examine a method in which the faulty condition is categorized into three levels. The measures taken to cope with the faulty condition are set for each level to enable the robot to continue to execute the task. We show experimental results using an omnidirectional mobile robot with a self-diagnosis system and our proposed method.     

Training to improve virtual team communication

Abstract. Organizations are utilizing virtual teams, comprising workgroup members who communicate and collaborate with technology, to accomplish tasks. These teams are geographically distributed and communicate via computer-mediated communication systems (CMCS), and may never or rarely meet face-to-face. Relational links among team members have been found to be a significant contributor to the effectiveness of information exchange in the use of CMCS. In most cases, team members receive little or no training to improve the effectiveness of this form of communication. When training is used, it often focuses on software utilization skills, not on interpersonal communication dynamics. This paper discusses the effect of virtual team communication training on group interactions, especially for enhancing these relational links and thereby improving communication and information exchange in virtual teams. It was found that teams that were given appropriate training exhibited improved perceptions of the interaction process over time, specifically with regard to trust, commitment and frank expression between members. Discussion of the role of training on virtual team processes and outcomes is discussed and future research implications are presented.