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.     

Millibots

Concerns the development of a framework and algorithms for a distributed heterogeneous robot team. Team members exchange sensor information, collaborate to track and identify targets, or even assist each other to scale obstacles. As for sensing, by coordinating its members a team can exploit information derived from multiple disparate viewpoints. A single robot, even though equipped with a large array of different sensing modalities, is limited at any one time to a single viewpoint, but a team of robots can simultaneously collect information from multiple locations. This article describes the design and construction of a team of 7 /spl times/ 7 /spl times/ 7-cm robots called "millibots". We show how the team can exploit collaboration to perform missions such as mapping, exploration, surveillance, and eventually support rescue operations.     

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.     

Symbiotic coevolutionary genetic programming: a benchmarking study under large attribute spaces

Classification under large attribute spaces represents a dual learning problem in which attribute subspaces need to be identified at the same time as the classifier design is established. Embedded as opposed to filter or wrapper methodologies address both tasks simultaneously. The motivation for this work stems from the observation that team based approaches to Genetic Programming (GP) have the potential to design multiple classifiers per class—each with a potentially unique attribute subspace—without recourse to filter or wrapper style preprocessing steps. Specifically, competitive coevolution provides the basis for scaling the algorithm to data sets with large instance counts; whereas cooperative coevolution provides a framework for problem decomposition under a bid-based model for establishing program context. Symbiosis is used to separate the tasks of team/ensemble composition from the design of specific team members. Team composition is specified in terms of a combinatorial search performed by a Genetic Algorithm (GA); whereas the properties of individual team members and therefore subspace identification is established under an independent GP population. Teaming implies that the members of the resulting ensemble of classifiers should have explicitly non-overlapping behaviour. Performance evaluation is conducted over data sets taken from the UCI repository with 649–102,660 attributes and 2–10 classes. The resulting teams identify attribute spaces 1–4 orders of magnitude smaller than under the original data set. Moreover, team members generally consist of less than 10 instructions; thus, small attribute subspaces are not being traded for opaque models.     

Enabling collaborative engineering and science at JPL

We examine the issue of distributed collaboration at the Jet Propulsion Laboratory (JPL). With the goals of “faster, better, cheaper” missions, an efficient, seamless collaboration capability is critical to future JPL space exploration missions. We assert that the current capabilities for distributed collaboration internal to JPL, as well as external, are unsatisfactory. This paper provides a vision of greatly enhanced distributed collaboration capabilities in the near future and into the far future. Our vision focuses primarily on distributed collaborative engineering and science.We believe enhanced capabilities are necessary in two collaborative paradigms: the virtual conference and the shared virtual workspace. We describe these collaborative paradigms, and discuss the tools that exist and the additional capability necessary to achieve the collaborative vision with respect to the types of data we typically work with at JPL. We identify the following types of data frequently exchanged in collaborative activities: project planning data, design data, notes/documentation, communication data, analysis/performance data, verification data and scientific data. Our analysis shows that at present there is good GroupWare support for project planning data and notes/documentation data. Support is improving for design data. Other data types have no or sporadic support at best.     

Multi-tasking arbitration and behaviour design for human-interactive robots

Robots that interact with humans in household environments are required to handle multiple real-time tasks simultaneously, such as carrying objects, collision avoidance and conversation with human. This article presents a design framework for the control and recognition processes to meet these requirements taking into account stochastic human behaviour. The proposed design method first introduces a Petri net for synchronisation of multiple tasks. The Petri net formulation is converted to Markov decision processes and processed in an optimal control framework. Three tasks (safety confirmation, object conveyance and conversation) interact and are expressed by the Petri net. Using the proposed framework, tasks that normally tend to be designed by integrating many if–then rules can be designed in a systematic manner in a state estimation and optimisation framework from the viewpoint of the shortest time optimal control. The proposed arbitration method was verified by simulations and experiments using RI-MAN, which was developed for interactive tasks with humans.     

A preliminary investigation of information systems team structures

Productivity in the information age is widely perceived to be a major organizational problem. One strategy for enhancing organizational productivity has been the use of task teams. Assignment to task teams is usually based on individual technical expertise, individual availability, and/or positional politics rather than on the effectiveness of the team members in the specific organizational situation. This paper investigations characteristics of team members and then examines the effect of these characteristics and the requirements of the organizational task on team effectiveness.The findings indicate that the perceptual types of team members and the task structure impacts team effectiveness. It lends evidence that heterogeneity of perceptual types is best for solving unstructured tasks whereas heterogeneity can be counter-productive when solving structured tasks. It also suggests that one team might not be appropriate for all stages of a project. As the structure of the tasks change, the optimum team composition might also change.     

An organizational approach to designing an intelligent knowledge-based system: Application to the decision-making process in design projects

Knowledge-based engineering (KBE) approaches are designed to reduce the time and cost of product development by capturing, retaining and re-using design knowledge. They currently focus on repetitive design tasks where knowledge is considered as a static resource. However, knowledge is intrinsically linked to the organizations and people who use it. Thus, to be efficient, these knowledge-based systems (KBS) have to be able to take into account all the mechanisms of knowledge creation, sharing and evaluation made by the users. Using the agent paradigm, new knowledge-based systems can be designed in order to address this research issue. Indeed, the agents have social abilities and are able to achieve very complex tasks. These two features are necessary for making a knowledge-based system efficient. However, there still exists today a lack of approaches and methodologies to help design such applications. This paper presents DOCK, a methodology to design an intelligent knowledge-based system that aims to support the knowledge management process. In order to take into account all the mechanisms of knowledge generation, sharing and re-use, DOCK is based on the hypothesis that efficient modelling of human organizations, by highlighting their roles, collaborations, skills, goals and knowledge, will help the KBS designer to specify an adapted knowledge-based system. Finally, DOCK is implemented to design the SMA SNOTRA that is dedicated to supporting a decision-making process for design projects.     

Dynamic Verification of Memory Consistency in Cache-Coherent Multithreaded Computer Architectures

Multithreaded servers with cache-coherent shared memory are the dominant type of machines used to run critical network services and database management systems. To achieve the high availability required for these tasks, it is necessary to incorporate mechanisms for error detection and recovery. Correct operation of the memory system is defined by the memory consistency model. Errors can therefore be detected by checking if the observed memory system behavior deviates from the specified consistency model. Based on recent work, we design a framework for dynamic verification of memory consistency (DVMC). The framework consists of mechanisms to verify three invariants that are proven to guarantee that a specified memory consistency model is obeyed. We describe an implementation of the framework for the SPARCv9 architecture, and we experimentally evaluate its performance using full-system simulation of commercial workloads.     

Measuring team situation awareness in decentralized command and control environments

Decentralized command and control settings like those found in the military are rife with complexity and change. These settings typically involve dozens, if not hundreds to thousands, of heterogeneous players coordinating in a distributed fashion in a dynamically networked battlefield laden with sensor data, intelligence reports, communications, and plans emanating from many different perspectives. Consider the concept of team situation awareness in this setting. What does it mean for a team to be aware of a situation or, more importantly, of a critical change in a situation? Is it sufficient or necessary for all individuals on the team to be independently aware? Or is there some more holistic awareness that emerges as team members interact? We re-examine the concept of team situation awareness in decentralized systems beyond an individual-oriented knowledge-based construct by considering it as a team interaction-based phenomenon. A theoretical framework for a process-based measure called 'coordinated awareness of situations by teams' is outlined.     

Decentralized planning and control for UAV–UGV cooperative teams

In this paper we study a symbiotic aerial vehicle-ground vehicle robotic team where unmanned aerial vehicles (UAVs) are used for aerial manipulation tasks, while unmanned ground vehicles (UGVs) aid and assist them. UGV can provide a UAV with a safe landing area and transport it across large distances, while UAV can provide an additional degree of freedom for the UGV, enabling it to negotiate obstacles. We propose an overall system control framework that includes high-accuracy motion planning for each individual robot and ad-hoc decentralized mission planning for complex missions. Experimental results obtained in a mockup arena for parcel transportation scenario show that the system is able to plan and execute missions in various environments and that the obtained plans result in lower energy consumption.     

Block off: an examination of new control room configurations and reduced crew sizes examining engineered production blocking

Previous research has shown a potential bottleneck of communication of information between the sonar controller (SOC) and operations officer (OPSO) in submarine sound and control rooms. This research aimed to see if this bottleneck could be removed by co-locating the sound and control room teams. Further, it also looked at the effects of reducing the crew numbers. Ten teams preformed the return to periscope depth tasks during high and low demand in a simulated submarine control room. Activities and communications of the teams were recorded and compared with data from a baseline condition of contemporary operations. The findings show that the co-location of the sound room and control room teams relieved the bottleneck of communications between the SOC and OPSO. Although communications increased, this was more balanced across team members and more relative to operational demand. This was coupled with more efficient task completion, resulting in greater number of tasks being completed by the command teams. Reduced crewing led to greater communications between the remaining members of the team together with task shedding in the higher demand condition. Future research should contrast these findings with objective measures of task performance to better understand potential performance benefits.     

基于FPGA可扩展的Mapreduce架构设计与实现

在基于机群的Mapreduce架构模型基础上,提出了一种基于CPU和FPGA环境、可扩展的Mapreduce架构。通过网络连接和驱动模块,实现了计算机软件与可编程硬件之间的通信,其中,CPU主机主要完成于文件系统的通行,将复杂耗时的运算过程转移到FPGA平台中处理,并引入内部流水线处理过程,大幅度加速了系统运算过程。同时,该架构可将更多的任务扩展到多个FPGA平台,弥补了器件内部存储资源的局限性,提高了系统的性能。此外,软硬件之间的命令、状态等信息交互为管理在FPGA中扩展任务提供了有效途径。实验证明,此架构在大幅提高运算速度的同时,提供了较好的底层设备可扩展性和管理的灵活性。     

Design and implementation of a multimedia CSCW platform

In this paper, a generic four-layer framework for computer supported cooperative work (CSCW) is proposed. With clear separation of functionalities in each layer of the framework, application developers could implement their specific CSCW applications easily. Based on the four-layer framework, the architecture of a general purpose CSCW platform is designed and implemented with the necessary functionalities to help the collaborations among group members. To provide the system with more features and user friendliness, multimedia processing and transmission capabilities for audio and video are incorporated into the platform. Features like application-sharing, group decision support, multimedia mail transmission, etc., are well implemented in the platform. Moreover, an efficient network transport protocol, called VXTP, is designed and implemented to avoid the transmission overhead of conventional TCP. The performance measurements using both VXTP and TCP are given in the paper for comparison. Lastly, compared with other CSCW systems, our design achieves greater flexibility and portability by adopting the generality philosophy in the framework.     

An algorithm for cooperative task allocation in scalable,constrained multiple robot systems

The current trends in the robotics field have led to the development of large-scale multiple robot systems, and they are deployed for complex missions. The robots in the system can communicate and interact with each other for resource sharing and task processing. Many of such systems fail despite the availability of necessary resources. The major reason for this is their poor coordination mechanism. Task planning, which involves task decomposition and task allocation, is paramount in the design of coordination and cooperation strategies of multiple robot systems. Task allocation mechanism allocates the task in a mission to the robots by maximizing the overall expected performance, and thereby reducing the total allocation cost for the team. In this paper, we formulate a heuristic search-based task allocation algorithm for the task processing in heterogeneous multiple robot system, by maximizing the efficiency in terms of both communication and processing cost. We assume a set of decomposed tasks of a mission, which needs to be allocated to the robots. The near-optimal allocation schemes are found using the proposed peer structure algorithm for the given problem, where the number of the tasks is more than the robots present in the system. The cost function is the summation of static overhead cost of robots, assignment cost, and the communication cost between the dependent tasks, if they are assigned to different robots. Experiments are performed to verify the effectiveness of the algorithm by comparing it with the existing methods in terms of computational time and quality of solution. The experimental results show that the proposed algorithm performs the best under different problem scales. This proves that the algorithm can be scaled for larger system and it can work for dynamic multiple robot system.     

Human-systems interaction for virtual environment team training

Virtual environments are increasingly used to support collaborative activities and distance learning. However, few are designed to support students, instructors and simulations in multi-participant team training. This paper describes the Training Studio, a system for authoring, delivering and evaluating multi-participant team training in an immersed virtual environment. The Training Studio focuses on human-systems interaction, allowing multiple students to learn and perform team tasks. The Training Studio supports collaborative learning for either single or multi-participant activity. This is accomplished through the use of agents which are assigned to students to act as personal mentors or missing team members. Conducting team training within a virtual environment introduces complexities and issues unique to team training and multiple-participant virtual environments. This paper describes our approach to virtual environment team training, discussing issues confronted and resulting design considerations and implementations.     

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).     

Experimental analysis of self-organizing team’s behaviors

This paper is focused on the study of self-organizing team’s behaviors which are dependent on the interaction rules and the decision factors of team members. The self-organizing team’s behavior means that team members work unconditionally with one of the three work attitudes (diligence, average, and shirking). A small-world network is suggested as the basic relationships of team members. Different from the traditional models, Reciprocators encourage their friends if they work diligently and punish them if they shirk work. It is supposed that team member’s decision of choosing work attitude depends on four decision factors, humanity, herd instinct, rationality, and follower tendency. Firstly, all of the four decision factors’ weights are supposed as 0.25. Multiple experiments were conducted to analyze the behavior of a team by a multi-agent experiment system. It is found that, in order to increase the fraction of diligent team members, different strategies should be used under different Reciprocators’ fractions. Increasing Reciprocators’ fraction is beneficial to the increase of diligent members; however, the increase rate will slow down after an inflexion (here it means the inflexion of Reciprocators’ fraction). After the previous experiments study, extended experiments were developed to work on the influence of the four factors’ different weights. A self-adaptive algorithm is suggested to achieve the four decision factors’ weights. The results of self-adaptive algorithm have different influences on the team’s behaviors under different fractions of Reciprocators. Finally, influences of members’ different relationships are studied by other experiments. It is also proved that the fraction of diligent members is not dependent on the structure of team members’ relationships. The results demonstrate that the self-organizing team’s behavior can be significantly influenced by its scenario while managing a self-organizing team.