Reactive direction control for a mobile robot: a locust-like control of?escape direction emerges when a?bilateral pair of model locust visual neurons are integrated

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to the image of an approaching object. These neurons are called the lobula giant movement detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the development of an LGMD model for use as an artificial collision detector in robotic applications. To date, robots have been equipped with only a single, central artificial LGMD sensor, and this triggers a non-directional stop or rotation when a potentially colliding object is detected. Clearly, for a robot to behave autonomously, it must react differently to stimuli approaching from different directions. In this study, we implement a bilateral pair of LGMD models in Khepera robots equipped with normal and panoramic cameras. We integrate the responses of these LGMD models using methodologies inspired by research on escape direction control in cockroaches. Using ‘randomised winner-take-all’ or ‘steering wheel’ algorithms for LGMD model integration, the Khepera robots could escape an approaching threat in real time and with a similar distribution of escape directions as real locusts. We also found that by optimising these algorithms, we could use them to integrate the left and right DCMD responses of real jumping locusts offline and reproduce the actual escape directions that the locusts took in a particular trial. Our results significantly advance the development of an artificial collision detection and evasion system based on the locust LGMD by allowing it reactive control over robot behaviour. The success of this approach may also indicate some important areas to be pursued in future biological research.     

A modified model for the Lobula Giant Movement Detector and its FPGA implementation

Bio-inspired vision sensors are particularly appropriate candidates for navigation of vehicles or mobile robots due to their computational simplicity, allowing compact hardware implementations with low power dissipation. The Lobula Giant Movement Detector (LGMD) is a wide-field visual neuron located in the Lobula layer of the Locust nervous system. The LGMD increases its firing rate in response to both the velocity of an approaching object and the proximity of this object. It has been found that it can respond to looming stimuli very quickly and trigger avoidance reactions. It has been successfully applied in visual collision avoidance systems for vehicles and robots. This paper introduces a modified neural model for LGMD that provides additional depth direction information for the movement. The proposed model retains the simplicity of the previous model by adding only a few new cells. It has been simplified and implemented on a Field Programmable Gate Array (FPGA), taking advantage of the inherent parallelism exhibited by the LGMD, and tested on real-time video streams. Experimental results demonstrate the effectiveness as a fast motion detector.     

Collision detection in complex dynamic scenes using an LGMD-based visual neural network with feature enhancement

The lobula giant movement detector (LGMD) is an identified neuron in the locust brain that responds most strongly to the images of an approaching object such as a predator. Its computational model can cope with unpredictable environments without using specific object recognition algorithms. In this paper, an LGMD-based neural network is proposed with a new feature enhancement mechanism to enhance the expanded edges of colliding objects via grouped excitation for collision detection with complex backgrounds. The isolated excitation caused by background detail will be filtered out by the new mechanism. Offline tests demonstrated the advantages of the presented LGMD-based neural network in complex backgrounds. Real time robotics experiments using the LGMD-based neural network as the only sensory system showed that the system worked reliably in a wide range of conditions; in particular, the robot was able to navigate in arenas with structured surrounds and complex backgrounds.     

A model-based sound localization system and its application to robot navigation

This paper describes a mobile robot equipped with a real time sound localization system as well as a sonar system for obstacle detection. The sound localization method is based on a model of the precedence effect of the human auditory system to cope with echoes and reverberations. Sound localization and robot navigation experiments were conducted. The results show that the robot is capable of localizing sounding objects in a reverberant environment and approaching the objects without collisions, even when the objects were behind obstacles. Environment flexibility and error robustness of the system were discussed as well.     

基于消息中间件的持久状态服务扩展模型

本文提出了一个基于消息中间件的持久状态服务的扩展模型。与原持久状态服务不同的是本扩展模型增加了缓存管理，而且它是建立在基于内容订阅方式的消息中间件之上的。它不但移去了原持久状态服务频繁访问存储器而产生的瓶颈问题，而且以一种松散耦合的方式实现了在分布式信息系统中的持久对象数据的共享。     

Extending Superquadrics with Exponent Functions: Modeling and Reconstruction

Superquadrics are a family of parametric shapes which can model a diverse set of objects. They have received significant attention because of their compact representation and robust methods for recovery of 3D models. However, their assumption of intrinsical symmetry fails in modeling numerous real-world examples such as the human body, animals, and other naturally occurring objects. In this paper, we present a novel approach, which is called extended superquadric, to extend superquadric's representation power with exponent functions. An extended superquadric model can be deformed in any direction because it extends the exponents of superquadrics from constants to functions of the latitude and longitude angles in the spherical coordinate system. Thus, extended superquadrics can model more complex shapes than superquadrics. It also maintains many desired properties of superquadrics such as compactness, controllability, and intuitive meaning, which are all advantageous for shape modeling, recognition, and reconstruction. In this paper, besides the use of extended superquadrics for modeling, we also discuss the recovery of extended superquadrics from 3D information (reconstruction). Experiments on both realistic modeling and extended superquadric fitting are presented. Our results are very encouraging and indicate that the use of extended superquadric has potential benefits for the generation of synthetic images for computer graphics and that extended superquadric also is a promising paradigm for shape representation and recovery in computer vision.     

SEMANTIC CONSTRAINT MODELER FOR 2D AND 3D GEOMETRY

Design changes for 2D & 3D geometry are the most important features in the process ofproduct design.Constraint modeling for variationl geometry based on geometric reasoning is one ofthe best approaches for this goal.However,it is difficult for the proposed systems to maintain orhandle the consistency and completeness of the constraint model of the design objects.To changethis situation,a semantic model and its control approach are presented,aiming at the integrationof the data,knowledge and method related to design objects.Aconstraint definition system for in-teractively defining the semantic model and a prototype modeler based on the semantic model arealso implemented to examine the idea which is extended to 3D geometric design too.     

Modelling and simulation of nabla fractional dynamic systems with nonzero initial conditions

The paper focuses on the numerical approximation of discrete fractional order systems with the conditions of nonzero initial instant and nonzero initial state. First, the inverse nabla Laplace transform is developed and the equivalent infinite dimensional frequency distributed model of discrete fractional order system is introduced. Then, resorting the nabla discrete Laplace transform, the rationality of the finite dimensional frequency distributed model approaching the infinite one is illuminated. Based on this, an original algorithm to estimate the parameters of the approximate model is proposed with the help of vector fitting method. Additionally, the applicable object is extended from a sum operator to a general system. Three numerical examples are performed to illustrate the applicability and flexibility of the introduced methodology.     

On model typing

Where object-oriented languages deal with objects as described by classes, model-driven development uses models, as graphs of interconnected objects, described by metamodels. A number of new languages have been and continue to be developed for this model-based paradigm, both for model transformation and for general programming using models. Many of these use single-object approaches to typing, derived from solutions found in object-oriented systems, while others use metamodels as model types, but without a clear notion of polymorphism. Both of these approaches lead to brittle and overly restrictive reuse characteristics. In this paper we propose a simple extension to object-oriented typing to better cater for a model-oriented context, including a simple strategy for typing models as a collection of interconnected objects. We suggest extensions to existing type system formalisms to support these concepts and their manipulation. Using a simple example we show how this extended approach permits more flexible reuse, while preserving type safety.     

基于PID神经网络的滑翔增程制导炮弹解耦控制系统设计

针对低速旋转的滑翔增程制导炮弹存在的俯仰和偏航通道控制耦合性问题,阐述利用基于PID神经网络进行双通道解耦控制设计。首先描述滑翔增程炮弹动力学模型,基于对该模型的分析基础上提出PID神经网络的结构和计算方法,并采用增加动量项的权值修正和自适应可变学习率对其进行改进。在此基础上,通过粒子群优化算法对网络的初始权值进行优化...     

面向多客体的细粒度RBAC模型及应用

从综合信息管理系统以及软件系统集成的需求出发,分析了NIST RBAC模型的局限性,在此基础上对其模型进行扩充,提出ERBAC模型。该模型适用于多种客体且具体客体不确定的情况。文章还给出了ERBAC模型的具体定义和应用实例。     

基于对象数据模型的高速公路GIS-T系统的研究与实现

针对传统GIS系统无法表达高速公路管理中对象之间的复杂关系这一问题,对GIS数据模型进行了研究,建立了基于符合OpenGIS抽象规范的几何数据模型的高速公路地理对象数据模型,实现基于对象数据模型的高速公路GIS-T系统来增强传统GIS系统的数据表达能力.能力提高后的系统,在高速公路管理者来看完全符合高速公路管理规范的,在二次开发用户或再次扩展系统功能程序员来看完全采用面向对象的,在面对地图操作的用户来看几乎表现真实世界的地理实体和逻辑对象的.     

Navigation of an AUV for investigation of underwater structures

There is a great demand for autonomous underwater vehicles (AUVs) to investigate artificial underwater structures such as piles and caissons in harbours, and risers and jackets of deep-sea oilfields. This paper proposes an autonomous investigation method of underwater structures using AUVs that is implemented by initially detecting the target objects, localizing them, then approaching them by taking video images while closely tracing their shape. A laser ranging system and a navigation method based on the relative position with respect to the target objects are introduced to realize this behaviour.     

An Extended Relational Data Model for Multimedia DBMSs

We have extended the canonical relational data model to enable the management of multimedia objects. In an attempt to provide a smooth paradigm shift to multimedia information system development, we have enhanced the relational data model framework with techniques for modeling, storing and manipulating multimedia data. In particular, we have provided a graphical conceptual model for structuring a multimedia document and mapping rules for translating it into an extended relational data schema. Extensions have regarded the management of foreign keys, active components, mechanisms for the management of spatial and temporal relations, and finally functions for handling multimedia presentations. As a consequence, we have also provided extensions to the SQL language to handle these new mechanisms.     

MOPNet：基于模块对象的Petri网模拟及其应用实例

本文把向对象的思想同扩充了的Ｐｅｔｒｉ网相结合，构造了基于模块对象的Ｐｅｔｒｉ网模拟方法ＭＯＰＮｅｔ，用于并发系统的建模，并给出了ＣＡＩ通信模型设计和实现的一个应用实例。     

Extended object model for product configuration design

This paper presents an extended object model for case-based reasoning (CBR) in product configuration design. In the extended object model, a few methods of knowledge expression are adopted, such as constraints, rules, objects, etc. On the basis of extended object model, case representation model for CBR is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of CBR in product configuration design, such as case representation, indexing, retrieving, and case revising. The presented model is an extension of the traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in case retrieving, and solution class used in case revising. Therefore, the product configuration knowledge used in the product configuration design can be represented by using this model. In the end, a metering pump product configuration design system is developed on the basis of the proposed product configuration model to support customized products.     

基于角色的扩展可管理访问控制模型研究与实现

基于角色的访问控制(RBAC)具有简单灵活、细粒度控制、可用性强等特点,受到广泛的关注,近10年来,RBAC得到了广泛的研究与扩展．针对RBAC模型中存在的不足,提出了一种基于角色的可管理访问控制模型EARBAC．EARBAC通过对客体资源、访问类型的进一步抽象,对NISTRBAC参考模型进行了有效的扩展,更具通用性与更强的现实世界表达能力,同时与ARBAC96的结合,使其具有良好的可管理能力．基于该扩展模型,实现了一个安全的网络文件原型系统．     

Web信息系统中统一细粒度访问控制的研究

为了实现Web信息系统的细粒度访问控制,研究了MVC(Model-View-Controller)构建模式,然后分别从视图层和控制层上考虑客体的结构和形式,在NIST RBAC的基础上提出了OHRBAC(Object Hierarchy RBAC)模型,并基于该模型分别利用JSP标签技术和AOP技术实现了视图层和控制层的细粒度访问控制,并抽象出Java Web信息系统中细粒度访问控制的一般解决方案,该方案安全性高、操作方便、可以快速部署、可扩展、可伸缩.     

3-D object decomposition with extended octree model and its application in geometric simulation of NC machining

The paper discusses the development of a prototype solid modeling system based on the extended octree modeling approach and its applications in 3-D NC machining simulation and automatic verification. Along with a simple hierarchical data structure, the extended octree model uses the face boundary information (i) to represent complex objects, (ii) to improve object representational accuracy, and (iii) to accelerate the model updating procedures in a graphic simulation process. The improved representational accuracy makes it possible to carry out automatic NC program verification by generating the machined model of the part through the simulation and comparing it with the designed model of the part. The paper also addresses the issues of model conversions from CSG and B-Rep schemes to the corresponding extended octree models and the issues of carrying out Boolean operations on those extended octree models. A prototype system has been implemented and is integrated with AutoCAD AME solid modeler for object modeling and for NC simulation purpose.     

A mixed analog–digital vision sensor for detecting objects approaching on a collision course

Bio-inspired vision system is a particularly good candidate for navigation of mobile robots and vehicles because of its computational advantages, e.g., low power dissipation and compact hardware. Previously, we had designed a mixed analog–digital integrated vision system for collision detection inspired by a locust neuronal circuit model. The response of the system was, however, susceptible to the luminance of approaching objects and the vibratory self-motion of a car when it was installed on a miniature mobile car. In the present study, we developed a new collision detection algorithm to overcome these problems based on robust image-motion detection and applied the algorithm to control a miniature mobile car.