An Implementation and Design of COMOR System for OOM Reuse

In the paper is highlighted the industrial objects as cars, spacecraft, telescopes, plotters, lasers, elevators, etc., which are described by the mathematical model with double astatism. These models of control objects have a double pole in the origin of the coordinate axes. In order to tune the PID controller to the model of object with double astatism, it was elaborated the tuning algorithm based on the maximum stability degree method with iterations. It was done the computer simulation of the automatic control system with the respectively model of object and PID controller and it was done the analysis of the obtained performance. The advantages of the maximum stability degree method with iterations were highlighted by the reducing calculations and time, which lead to the procedure simplification of the PID controller tuning.

Behavior of geographic objects holds a critical role in spatial databases. This, along with objects' position and space-varying attributes form a minimal set of concepts sufficient to capture spatial peculiarities in terms of the object-oriented rationale. We present the semantics and the graphical notation of a prototypical object-oriented model for the conceptual design of spatial databases: by extending the Object Model of the Object Modeling Technique to the Geographic Object Model, we show how the above three concepts fit naturally into any objectoriented tool. We augment this model with the constructs of spatial aggregation and spatial grouping to express the critical aspects of space-varying attributes, object boundary fuzziness and uncertainty, spatial relationships, and attribute generalization. Our proposal integrates the field- and object-based geographic views in one model. The principal idea behind this effort is the incorporation of a set of concepts into any semantic or object-oriented model in order to make them communicate at the conceptual level (semantic interoperability).

Level set methods were proposed mainly by mathematicians for constructing a model of a 3D object of arbitrary topology. However, those methods are computationally inefficient due to repeated distance transformations and increased dimensions. In the paper, we propose a new method of modeling fast objects of arbitrary topology by using a surface evolution approach based on mathematical morphology. Given sensor data covering the whole object surface, the method begins with an initial approximation of the object by evolving a closed surface into a model topologically equivalent to the real object. The refined approximation is then performed using energy minimization. The method has been applied in several experiments using range data, and the results are reported in the paper. © 2002 Wiley Periodicals, Inc. Syst Comp Jpn, 33(9): 58–67, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.1152

A comparison of the object model underpinning open systems interconnection (OSI) network management standards with that being developed for object-oriented software development systems indicates a close alignment between the models. But the OSI object-model goes further: it supports notions of asynchronously occurring events, concurrency, and optionality of implementation. These features are not found in the OMG object-model, but neither are they precluded. Consequently, the way is paved for network-management product suppliers to use OMG-conformant software-development systems. >

Active object-oriented database systems (AOODBSs) are based on the object-oriented paradigm and provide an event driven behavior for implementing time critical reactions by integrating event-condition-action (ECA) rules to the database. We focus on the modeling aspects of AOODBSs. We propose an integrated approach, called A/OODBMT (Active Object-Oriented Database Modeling Technique), which integrates and extends the Object Modeling Technique (OMT) method for conceptually designing active object-oriented database applications. A/OODBMT models database applications by defining and integrating four new types of models, namely the nested object model (NOM), the behavior model (BM), the nested rule model (NRM), and the nested event model (NEM).

Work objective is to develop a patentable design of locomotive traction drive mechanisms using the example of a suspension unit. Research methods: object modeling method, analytical methods for calculating dynamics of rolling stock. Research results and novelty: the design of the railway electric motor suspension unit, which will reduce costs in the course of maintenance and repair of a locomotive with a solid gear by increasing the reliability of the suspension unit parts, eliminating their wear, has been developed; a compensation coupling device has been devised. We will synthesize the object model of a technical system based on the identification of its typical structure by classifying technical systems. Conclusion: the application of the object modeling method together with the object model allows avoiding errors in the development of new designs of technical objects based on existing comparables and eliminates defects of the selected prototype. The use of the object modeling method makes it possible to synthesize patentable designs of the locomotive underframe mechanisms.

This article proposes a SLAM algorithm referred to as RGBD-Sphere SLAM. The key innovation of this work is the prototypical system that demonstrates how formal models of 3D geometric shape and appearance can be transformed into generative classification models that detect and recognize these shapes. Object models are specified as shape programs in PSML; a custom-built procedural language for 3D object modeling. Classifiers for each PSML shape are created by simulating how instances of each shape manifest in real-world sensor data, e.g., color images and range images. The proposed RGBD-Sphere SLAM algorithm demonstrates a prototypical example of the system. Here, the PSML program specifies spherical 3D objects having diffuse surface albedos and distinct color appearances. A recognizer uses PSML models of each object's geometry and appearance to detect instances of these objects within streaming RGBD sensor data. The detected model parameters are then integrated into an RGBD SLAM algorithm; hence the name RGBD-Sphere SLAM. This article describes the PSML programs, the spherical detection and recognition algorithms used, and describes the impact this approach has for improving the performance of RGBD SLAM approaches by incorporating detected objects as landmarks. This is the first example of a prototypical system that externalizes the geometric and appearance modeling to a programming language from which a recognizer is created, and marks an important step towards enabling users to “program” their problem space and allow computers to transform the formal object models, as expressed in PSML, into customized classifiers suited for specific sensor suites, e.g., color imagery and depth imagery.

To understand a large and complicated system, its specifier and user should be able to separate essential concerns from irrelevant details. To do that, specification of behavioral semantics-as opposed to just signatures (i.e., syntax)-is essential. Abstract and precise specifications are the corner stones of object modeling. However, object modeling has usually considered only behavior of isolated objects. Real-world enterprises do not consist only of isolated objects. It is the joint behavior of associated objects that defines the object model of the enterprise and therefore makes the business understandable. The paper show how semantics of an information model (the result of analyzing the system) can be specified in an abstract and precise manner, by reusing programming methodology concepts, and how this approach to specification is used in standardization activities. >

It is important to enable a robot to manipulate a target object that has no 3-D model information and is situated in an environment with other unknown objects nearby. This poses an open problem of how to combine perception and manipulation to enable the robot to build an appearance-based model of the target object on the spot to facilitate further manipulation of the object while avoiding the other unknown obstacles in the way. In this paper, we introduce an approach to enable a continuum manipulator, which is apt to maneuver through a crowded environment, to gradually build a 3-D surface model of the target object by moving an RGB-D sensor around the object while also detecting and avoiding surrounding unknown obstacles. Our approach interleaves perception and manipulation such that perception guides the manipulator movement, which in turn allows more perception of the target object for object model building and further manipulator motion. Our approach is characterized by a progressive strategy to register RGB-D images of the target object to build and extend a partial model of the object and the corresponding motion planning strategy for the continuum robot to carry out model building and avoid obstacles at the same time. To demonstrate the effectiveness of our approach, experiments on progressive model building of real objects from real RGB-D images are conducted, where a simulated continuum robot plans and executes its motion to carry the RGB-D camera around a target object for taking those images in an augmented reality setting.

Object-oriented modelling is an established approach to document the information systems. In an object model, a system is captured in terms of object types and associations, state machines, collaboration diagrams, etc. Process modeling on the other hand, provides a different approach whereby behaviour is captured in terms of activities, flow dependencies, resources, etc. These two approaches have their relative advantages. In object models, behaviour is split across object types, whereas in process models, behaviour is captured along chains of logically related tasks. Also, object models and process models lend themselves to different styles of implementation. There is an opportunity to leverage the relative advantages of object models and process models by creating integrated meta-models and transformations so that modellers can switch between these views. In this paper we define a transformation from a meta-model for object behavior modeling to a meta-model for process modeling. The transformation relies on the identification of causal relations in the object model. These relations are encoded in a heuristics net from which a process model is derived.KeywordsProcess modelobject modelmodel transformation

This paper presents an approach to acquire textured 3D models of objects without the need for sophisticated hardware infrastructures. The approach is inexpensive, using a low-cost Microsoft Kinect RGB-D sensor and Augmented Reality (AR) markers printed on paper sheets. The AR-markers can be freely placed in the scene, allowing the modeling of objects of various sizes, and the sensor can be moved by the hand of an untrained person. To generate usable models with this very inexpensive and simple setup, the sequence of RGB-D scans is embedded in a graph-based optimizer for automatic post-refinement. The main novelty of this contribution is the development of an uncertainty model for an AR-marker. The AR-marker uncertainty models are used as constraints in an optimization problem to better estimate the object pose. The models are in the end further fine-tuned by a standard point-based registration algorithm. The results section presents realistic models of various objects generated using this system, e.g., parcels, sport balls, human dolls etc. Additionally, a quantitative analysis is presented using objects of known dimensions.

There is a growing interest in adopting object technologies for the development of real-time control systems. Several commercial tools, currently available, provide object-oriented modeling and design support for real-time control systems. While these products provide many useful facilities, such as visualization tools and automatic code generation, they are all weak in addressing the central characteristic of real-time control systems design, i.e., providing support for a designer to reason about timeliness properties. We believe an approach that integrates the advancements in both object modeling and design methods and real-time scheduling theory is the key to successful use of object technology for real-time software. Surprisingly several past approaches to integrate the two either restrict the object models, or do not allow sophisticated schedulability analysis techniques. This study shows how schedulability analysis can be integrated with UML for Real-Time (UML-RT) to deal with timing properties in real time control systems. More specifically, we develop the schedulability and feasibility analysis modeling for the external messages that may suffer release jitter due to being dispatched by a tick driven scheduler in real-time control system and we also develop the scheduliablity modeling for sporadic activities, where messages arrive sporadically then execute periodically for some bounded time. This method can be used to cope with timing constraints in realistic and complex real-time control systems. Using this method, a designer can quickly evaluate the impact of various implementation decisions on schedulability. In conjunction with automatic code-generation, we believe that this will greatly streamline the design and development of real-time control systems software.

An integrated approach to CAD: modelling concepts in building design and construction

Creation of complex technical objects (CTO, such as science-intensive engineering objects, which are characterized by the number of elements and connections equal to 106 and more) – a process containing long subprocesses, complex objects, models, and based on available standards and information technology (IT). It is known from practice that CTO models are created with the help of information systems - components of CALS and PLM-solutions. This process have the following shortcomings: models at different stages of creation of CTO are not completely interconnected; CTO modeling takes place using different components of IT CALS and PLM-solutions, which creates constant difficulties in data conversion and leads to partial or complete loss of model data; there is no automated communication with other CTO models.
 A generalized model of complex technical objects is proposed, which based on using the theoretical-multiple approach allows to establish an information connection between the models of the process of creating complex technical objects. The information system of creation of the generalized model of difficult technical objects that allowed automating process of processing and construction of models is developed; to supplement the technology of parallel PLM design and components of information technologies CALS and PLM-solutions for the task of creating models of complex technical objects.

Object shape information is an important parameter in robot grasping tasks. However, it may be difficult to obtain accurate models of novel objects due to incomplete and noisy sensory measurements. In addition, object shape may change due to frequent interaction with the object (cereal boxes, etc). In this paper, we present a probabilistic approach for learning object models based on visual and tactile perception through physical interaction with an object. Our robot explores unknown objects by touching them strategically at parts that are uncertain in terms of shape. The robot starts by using only visual features to form an initial hypothesis about the object shape, then gradually adds tactile measurements to refine the object model. Our experiments involve ten objects of varying shapes and sizes in a real setup. The results show that our method is capable of choosing a small number of touches to construct object models similar to real object shapes and to determine similarities among acquired models.