航天器多维动态可配置健康管理系统设计

以工程任务为牵引,提出了一种基于多维动态可配置模型的航天自主健康管理及控制系统设计与实现方法,有效解决了不同航天器间自主控制管理需求差异大、开发效率低等问题,具有一定的创新性。阐述了系统的设计思路,并给出实现示例,通过参数的动态表格化配置、判据的多源拟合等设计,实现健康管理规则库的构建;通过数据有效性服务的设计,完成对航天器健康状态判断数据源的质量控制;无差别异常检测模块、异常隔离与恢复等模块的设计,保障了航天器异常状态的实时处置,确保航天器安全运行。通用化的模型设计可支持不同航天器的自主健康管理及控制系统,已获得多个型号整器级测试应用验证,具有推广价值。     

A dynamical system approach to realtime obstacle avoidance

This paper presents a novel approach to real-time obstacle avoidance based on Dynamical Systems (DS) that ensures impenetrability of multiple convex shaped objects. The proposed method can be applied to perform obstacle avoidance in Cartesian and Joint spaces and using both autonomous and non-autonomous DS-based controllers. Obstacle avoidance proceeds by modulating the original dynamics of the controller. The modulation is parameterizable and allows to determine a safety margin and to increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle. The method is validated in simulation on different types of DS including locally and globally asymptotically stable DS, autonomous and non-autonomous DS, limit cycles, and unstable DS. Further, we verify it in several robot experiments on the 7 degrees of freedom Barrett WAM arm.     

Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns

This paper presents a real-time path planning algorithm that guarantees probabilistic feasibility for autonomous robots with uncertain dynamics operating amidst one or more dynamic obstacles with uncertain motion patterns. Planning safe trajectories under such conditions requires both accurate prediction and proper integration of future obstacle behavior within the planner. Given that available observation data is limited, the motion model must provide generalizable predictions that satisfy dynamic and environmental constraints, a limitation of existing approaches. This work presents a novel solution, named RR-GP, which builds a learned motion pattern model by combining the flexibility of Gaussian processes (GP) with the efficiency of RRT-Reach, a sampling-based reachability computation. Obstacle trajectory GP predictions are conditioned on dynamically feasible paths identified from the reachability analysis, yielding more accurate predictions of future behavior. RR-GP predictions are integrated with a robust path planner, using chance-constrained RRT, to identify probabilistically feasible paths. Theoretical guarantees of probabilistic feasibility are shown for linear systems under Gaussian uncertainty; approximations for nonlinear dynamics and/or non-Gaussian uncertainty are also presented. Simulations demonstrate that, with this planner, an autonomous vehicle can safely navigate a complex environment in real-time while significantly reducing the risk of collisions with dynamic obstacles.     

High-speed processing in wired-and-wireless integrated autonomous decentralized system and its application to IC card ticket system

The automatic fare collection systems need both high performance and high reliability. High performance is one of the most expected functions on the automatic fare collection gates (AFCGs) handling the highly dense passengers during rush hours. Reliability is also indispensable because the tickets are equivalent to money. For a wireless IC card ticket system, expected to improve the passengers’ convenience and to reduce the maintenance cost, is difficult to meet these two requirements because of wireless communications between an IC card and an AFCG. This paper introduces the autonomous decentralized system as the solution and how it is applied to the system. Then, two models are prepared and simulated to evaluate the efficiency, especially high-speed processing. The technologies are implemented into the “Suica” system at East Japan Railway Company and have proven the effectiveness.     

Iaso: an autonomous fault-tolerant management system for supercomputers

With the increase of system scale, the inherent reliability of supercomputers becomes lower and lower. The cost of fault handling and task recovery increases so rapidly that the reliability issue will soon harm the usability of supercomputers. This issue is referred to as the “reliability wall”, which is regarded as a critical problem for current and future supercomputers. To address this problem, we propose an autonomous fault-tolerant system, named Iaso, in MilkyWay-2 system. Iaso introduces the concept of autonomous management in supercomputers. By autonomous management, the computer itself, rather than manpower, takes charge of the fault management work. Iaso automatically manage the whole lifecycle of faults, including fault detection, fault diagnosis, fault isolation, and task recovery. Iaso endows the autonomous features with MilkyWay-2 system, such as self-awareness, self-diagnosis, self-healing, and self-protection. With the help of Iaso, the cost of fault handling in supercomputers reduces from several hours to a few seconds. Iaso greatly improves the usability and reliability of MilkyWay-2 system.     

Autonomous straightening and traversing of shipboard helicopters

This paper describes an investigation into autonomous shipboard helicopter maneuvering and traversing operations using the Aircraft/Ship Integrated Secure and Traverse (ASIST) recovery and handling system developed by Indal Technologies, Inc. The ASIST system continuously monitors the aircraft's position and orientation and provides a means of actuation to maneuver the helicopter on deck. This allows the possibility for completely autonomous aircraft securing, maneuvering, and traversing capability. An autonomous maneuvering algorithm offers the potential for automatically selecting the optimal maneuvering sequence and executing it with greater efficiency and reliability than can be achieved by a human operator. The proposed method takes advantage of the position and orientation of the helicopter measured by the existing Helicopter Position Sensing Equipment thereby not requiring additional sensors on the actual helicopter. The paper presents the development and validation of the autonomous straightening and traversing algorithms using a nonlinear on‐deck helicopter maneuvering simulation and the Carleton Experimental Shipboard Helicopter Interface Platform.     

一个计算机生成角色的行进避障算法

文章对计算机生成角色在分布式虚拟环境中行进时的障碍规避进行了研究。避障是计算机生成角色在行进中对各种障碍物的实时处理过程,文中给出了一个计算机生成角色的避障算法,对虚拟环境中不同类型的实体发生的可能碰撞采取了不同的避撞策略,着重研究了多个计算机生成角色间避障的方法;与已有的一些研究不同,笔者提出了可能障碍区和可能障碍集的概念,在此基础上对多个计算机生成角色产生可能障碍区后进行了实时处理;文中还给出了算法的正确性证明和时间复杂度分析。使用这个算法,可使计算机生成角色在虚拟环境中的行进行为更加逼真。     

Virtual tools that carry attributes for interactively specifying intermediate manufacturing processes

This paper describes an interactive system for specifying robotic tasks using virtual tools that allow an operator to reach into a live video scene and direct robots to use corresponding real tools in complex scenarios that involve integrating a variety of otherwise autonomous technologies. The attribute rich virtual tools concept provides a human-machine interface that is robust to unanticipated developments and tunable to the specific requirements of a particular task. This Interactive Specification concept is applied to intermediate manufacturing tasks.     

Predictive Guidance-Based Navigation for Mobile Robots: A Novel Strategy for Target Interception on Realistic Terrains

This paper presents a novel online trajectory planning method for the autonomous robotic interception of mobile targets in the presence of dynamic obstacles. The objective is time-optimal position and velocity matching (also referred to as rendezvous) while traversing realistic terrains with uneven topologies. The primary novelty of the proposed interception method lies in its ability to minimize rendezvous time with the target, as well as energy consumption, by directly considering the dynamics of the obstacles and the target while accurately determining a feasible way to travel through the realistic terrain. This objective is achieved by computing rendezvous maneuvers using an advanced predictive guidance law. The method is designed to effectively cope with maneuvering targets/obstacles by predicting their future velocities and accelerations. Obstacle avoidance and terrain navigation are seamlessly integrated. Extensive simulation and experimental analyses, some of which are reported in this paper, have clearly demonstrated the time efficiency of the proposed rendezvous method.     

基于LSTM-OCSVM的无人机传感器数据异常检测

无人机是一种典型的依靠通信和控制系统实现自主飞行的信息物理系统,在安全性和可靠性方面引起了广泛的关注.本文考虑无人机传感器易受网络攻击问题,充分利用数据的时间相关性,提出了针对无人机传感器数据的异常检测模型.首先采用LSTM神经网络对传感器数据进行预测,再将预测值与实际值做差,并将差值输入LSTM分类器进行训练得到包含...     

Model predictive control for systems with stochastic multiplicative uncertainty and probabilistic constraints

Robust predictive control handles constrained systems that are subject to stochastic uncertainty but propagating the effects of uncertainty over a prediction horizon can be computationally expensive and conservative. This paper overcomes these issues through an augmented autonomous prediction formulation, and provides a method of handling probabilistic constraints and ensuring closed loop stability through the use of an extension of the concept of invariance, namely invariance with probability p.     

自主式微小型移动机器人群体行为进化的研究

自主式微小型移动机器人群体面临的一些环境常常是未知的、无结构的,同时由于其 自身体积大小的限制,在目前的工业水平上也很难在其上安装一些较为先进的传感器,以致 机器人仅能获取局部的信息,这些原因使得采用传统基于任务的设计方法将十分困难,而采 用基于行为的设计方法时,也很难保证所设计的机器人行为的有效性,为此本文采用了遗传 算法,随机产生了机器人群体中各初始个体的障碍物回避行为及机器设备故障排除行为,当 群体在特定的工作环境中仿真运行时,根据环境的情况和所需实现的任务,使群体行为性能 达到了较为优化的目的．     

Guaranteed infinite horizon avoidance of unpredictable,dynamically constrained obstacles

This paper presents a new approach to guaranteeing collision avoidance with respect to moving obstacles that have constrained dynamics but move unpredictably. Velocity Obstacles have been used previously to plan trajectories that avoid collisions with obstacles under the assumption that the trajectories of the objects are either known or can be accurately predicted ahead of time. However, for real systems this predicted trajectory will typically only be accurate over short time-horizons. To achieve safety over longer time periods, this paper instead considers the set of all reachable points by an obstacle assuming that the dynamics fit the unicycle model, which has known constant forward speed and a maximum turn rate (sometimes called the Dubins car model). This paper extends the Velocity Obstacle formulation by using reachability sets in place of a single “known” trajectory to find matching constraints in velocity space, called Velocity Obstacle Sets. The Velocity Obstacle Set for each obstacle is equivalent to the union of all velocity obstacles corresponding to any dynamically feasible future trajectory, given the obstacle’s current state. This region remains bounded as the time horizon is increased to infinity, and by choosing control inputs that lie outside of these Velocity Obstacle Sets, it is guaranteed that the host agent can always actively avoid collisions with the obstacles, even without knowing their exact future trajectories. Furthermore it is proven that, subject to certain initial conditions, an iterative planner under these constraints guarantees safety for all time. Such an iterative planner is implemented and demonstrated in simulation.     

Expectation-based selective attention for visual monitoring and control of a robot vehicle

Reliable vision-based control of an autonomous vehicle requires the ability to focus attention on the important features in an input scene. Previous work with an autonomous lane following system, ALVINN (Pomerleau, 1993), has yielded good results in uncluttered conditions. This paper presents an artificial neural network based learning approach for handling difficult scenes which will confuse the ALVINN system. This work presents a mechanism for achieving task-specific focus of attention by exploiting temporal coherence. A saliency map, which is based upon a computed expectation of the contents of the inputs in the next time step, indicates which regions of the input retina are important for performing the task. The saliency map can be used to accentuate the features which are important for the task, and de-emphasize those which are not.     

A model for software rework reduction through a combination of anomaly metrics

Analysis of anomalies reported during testing of a project can tell a lot about how well the processes and products work. Still, organizations rarely use anomaly reports for more than progress tracking although projects commonly spend a significant part of the development time on finding and correcting faults. This paper presents an anomaly metrics model that organizations can use for identifying improvements in the development process, i.e. to reduce the cost and lead-time spent on rework-related activities and to improve the quality of the delivered product. The model is the result of a four year research project performed at Ericsson.     

机器人及机器人学中的控制问题

机器人已成为进一步实现制造业、非制造业、军事活动以至家庭服务自动化的重要工具.机器人学则是更综合地研究如何使机器或系统具有“思想、感知或动作功能的一门交叉性新学科”.机器人的发展是波浪式的,经历了多次的曲折.目前工业机器人中除装配机器人外,其他点焊、弧焊、喷漆及搬运机器人,由于应用范围限制,以及工业生产装备更新速度和投资规模的影响,市场日趋饱和.以美国为例.制造商订单1984年达到高峰6046台.至1986年下降至5713台,不过对机器人未来市场大都持乐观态度.但进一步开拓市场.有待于推出适用于各种环境作业的各式各样的机器人.日本东京大学教授认为机器人当前处于又一次高潮的前夜(Nightmare),正是需要大力加强研究开发的时期.我国正在着手建立工业机器人产业,这一情况值得我们注意.本文着重从研究角度来介绍当前机器人及机器人学中的控制问题的现状及主要问题.     

A rule-based approach to proactive exception handling in business processes

Effectively handling exceptions in business process is an important capability of enterprises in the current global market environment, since their business processes are becoming more complex. Effective exception handling requires systematic support for the entire scope of exception handling: from exception prediction to exception prevention, and from exception detection to exception resolution. Most existing research approaches to exception handling in business process management and workflow areas have focused on reactive exception handling which resolves exceptions only after their occurrences. Therefore, a proactive exception handling approach is required to predict and prevent business process exceptions as early as possible before they occur, and detect and resolve exceptions as soon as possible after they occur. This paper presents comprehensive behavioral, functional, and informational requirements for proactive exception handling from the lifecycle perspective. Then, it proposes a rule language for proactive exception handling based on the requirements. The proposed rule language will enable effective and flexible exception handling by providing the information required for the entire scope of exception handling, especially, for exception prediction and prevention. Finally, the paper illustrates and validates the rule language with an example of exception prevention and a prototype system.     

Jgroup/ARM: a distributed object group platform with autonomous replication management

This paper presents the design and implementation of Jgroup/ARM, a distributed object group platform with autonomous replication management along with a novel measurement‐based assessment technique that is used to validate the fault‐handling capability of Jgroup/ARM. Jgroup extends Java RMI through the group communication paradigm and has been designed specifically for application support in partitionable systems. ARM aims at improving the dependability characteristics of systems through a fault‐treatment mechanism. Hence, ARM focuses on deployment and operational aspects, where the gain in terms of improved dependability is likely to be the greatest. The main objective of ARM is to localize failures and to reconfigure the system according to application‐specific dependability requirements. Combining Jgroup and ARM can significantly reduce the effort necessary for developing, deploying and managing dependable, partition‐aware applications. Jgroup/ARM is evaluated experimentally to validate its fault‐handling capability; the recovery performance of a system deployed in a wide area network is evaluated. In this experiment multiple nearly coincident reachability changes are injected to emulate network partitions separating the service replicas. The results show that Jgroup/ARM is able to recover applications to their initial state in several realistic failure scenarios, including multiple, concurrent network partitionings. Copyright © 2007 John Wiley & Sons, Ltd.     

Safer asynchronous runtime monitoring using compensations

Asynchronous monitoring relieves the system from additional overheads induced through online runtime monitoring. The price paid with such monitoring approaches is that the system may proceed further despite having reached an anomalous state. Any actions performed by the system after the error occurring are undesirable, since for instance, an unchecked malicious user access may perform unauthorized actions. In this paper we investigate the use of compensations to enable the undoing of such undesired actions, thus enriching asynchronous monitoring with the ability to restore the system to the original state just after the anomaly had occurred. Furthermore, we show how adaptive synchronisation and desynchronisation of the monitor with the system can also be achieved and report on the use of the proposed approach on an industrial case study of a financial transaction handling system.