Progressive object modeling with a continuum manipulator in unknown environments

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.

This study is to design a system of object-oriented model (OOM) reuse. This enhance the efficiency of software reuse through expressing object model utilizing cases, retrieving object model which is reused and developing object modeling procedure. We developed object model reuse system by case-based reasoning, called case-based object model reuse system (COMOR System). This system consists of four subsystems: the graphic user interface to interact with end-user, the object-oriented model management system to build a new object model, the case base to store the past object models, and the knowledge base to store object-oriented modeling and reusing knowledge.

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

The monograph is devoted to the system analysis of approaches to the building of models of chemical-technological systems, on the basis of which a systematic concept of building of models and the issues of solving decision-making problems for managing the operating modes of technological objects is proposed. The problems of the development of mathematical models and the optimization of complex chemical-technological systems are investigated, using the example of technological objects of oil refining, in conditions of uncertainty caused by the lack of reliable quantitative information and the fuzziness of available information. The structure of the monograph consists of an introduction, the main part of four sections, a conclusion and a list of sources of information. In the main part of the work, the current state of the problems of mathematical modelling of technological objects of oil refining production is analyzed. Methods of mathematical modelling and decision-making in the management of technological objects according to environmental and economic criteria are chosen as the direction of research. Methods of building mathematical models of chemical-technological systems of oil refining in a fuzzy environment have been investigated and proposed, and models of the technological complex of the catalytic reforming unit have been developed. An approach to the creation of a package of models for system modelling of the technological complex of the catalytic reforming unit is described. An algorithm for the synthesis of models of a technological complex of oil refining based on fuzzy information is proposed. Expert assessments have been carried out to develop a mathematical description of the technological complex of the reforming unit, a method has been developed for carrying out expert procedures in a fuzzy environment. The formulations of decision-making problems for the control of the technological complex of the reforming unit are formulated and, based on the modification of various optimality principles, heuristic algorithms for their solution are developed. The properties of the developed algorithms for solving decision-making problems have been investigated and a method for their selection in solving specific production problems has been proposed. A mathematical formulation of the decision-making problem for optimizing the operating modes of the catalytic reforming unit in a fuzzy environment is obtained and the results of its solution based on the proposed fuzzy approach are presented. The structure is created and the main functional blocks of the computer decision support system based on the object models are described. The issues of software implementation of the developed models are considered and a description of the interface of the computer system for modelling the units of the reforming unit and decision support for optimizing their operation modes is given.

Objective. Pre-stimulus effects of extreme personal valence on the perception of an ambivalent person.Background. The purpose of modern information technologies is not only to inform, but also to form certain views and opinions. These technologies are used in the media space, as well as in other areas of social interaction. The effects of behavioral conditioning, or priming, play an important role in the perception construction. At the same time, the question of the factors leading to its direct (assimilative) and inverse (contrast) effects remains poorly understood. Thus, any forecast of behavioral reactions in vivo becomes too imprecise.Study design. During the experiment, participants watched video interviews with a target object (male or female), who answered the Short Dark Triad questions, demonstrating the ambivalence of dark features. In two experimental groups, the perception of the target object was preceded by the presentation of an extremely “bad” or extremely “good” personality. In the control group, the target object was presented without pre-stimulus exposure. After viewing, the participants completed the Target Attitude Scale. The data were processed using ANOVA. Additionally, the effects of gender on the attitude variable were monitored.Participants. The sample consisted of 608 students from 17 to 35 years old (M=20.17, SD=1.53), including 173 men (28%) and 435 women (72%).Measurements. Short Dark Triad by D. Jones and D. Paulhus, adapted by M.S. Egorova et al., The Scale of the General Attitude to the Perceived Object by S.A. Shchebetenko et al.Results. The general attitude towards an ambivalent object, measured by the Scale of the General Attitude to the Perceived Object, becomes significantly more positive after presentation of a negative pre-stimulus, compared to the control and a positive pre-stimulus conditions (p<0.001). In the male sample, there is no significant effect of a negative pre-stimulus on the perception of a woman with an ambivalent representation of dark features (p>0.10).Conclusions. Pre-stimulus of extreme intensity can determine the contrast effect not only in perception of abstract object, but also in perception of ambivalent person. It is shown that the preliminary presentation of an extremely negative person shifts the assessment of the ambivalent person upward. An extremely positive person pre-stimulus does not make the same effect. The effect of a negative pre-stimulus is significant in the perception of men by women, but does not extend to the perception of women by men.

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. >

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.

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).

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. >

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.

The interactive grasp of robots can grasp the corresponding objects according to the user’s choice. Most interactive grasp methods based on deep learning comprise visual language and grasp detection models. However, in existing methods, the trainability and generalization ability of the visual language model is weak, and the robot cannot cope well with grasping small target objects. Therefore, this paper proposes a 6-DoF grasp detection method guided by visual language, which converts text instructions and RGBD images of the scene to be grasped into inputs and outputs for the 6-DoF grasp posture of the object corresponding to the text instructions. In order to improve the trainability and feature extraction ability of the visual language model, a multi-head attention mechanism combined with hybrid normalization is designed. At the same time, a local attention mechanism is introduced into the grasp detection model to enhance the global and local information interaction ability of point cloud data, thereby improving the grasping ability of the grasp detection model for small target objects. The method proposed in this paper first uses the improved visual language model to predict the plane position information of the target object, then uses the improved grasp detection model to predict all the graspable postures in the scene, and finally uses the plane position information to filter out the graspable postures of the target object. The visual language model and grasp detection model proposed in this paper have achieved excellent performance in various scenarios of public datasets while ensuring a specific generalization ability. In addition, we also conducted real grasp experiments, and the 6-DoF grasp detection method based on visual language guidance proposed in this paper achieved a grasp success rate of 95%.

This paper describes how two cameras were used to implement stereoscopic visual imaging through a robot vision system. Image processing was applied to construct a real-time stereoscopic image tracking system for use in robots. The target object was sought by image preprocessing. The deviation of the target object from the optical center of the two cameras was measured to calculate the stereoscopic image depth of the target object, and the target object was instantly locked for real-time tracking. This system consists of two parts. The first part uses depth calculation to determine the distance between the target object and robot platform and applies image processing to simplify the image. The deviation angles of the left and right images are subsequently measured to calculate the target object distance. The second part uses real-time image tracking so that the platform can lock the image of the target object into an overlapping image. Proportional–integral–derivative (PID) feedback controls the robot movement and instantly obtains the target object and offset direction. The signal is exported to dc servo motors to drive the rotation of the two cameras and the movement of the platform. The image of the target object is locked in the image center of the stereoscopic visual system for real-time tracking.

<p>Continuum robots (CRs) have been the subject of intensive researches in recent years because of the wide range of their potential applications. One main domain of application is CR-based grasp, which needs studying grasp taxonomy and grasp synthesis. Despite the importance of these two topics for robotic operations, their concepts for CRs remain to be investigated. The first contribution of this thesis is to present a comprehensive CR-based grasp taxonomy. Grasp taxonomy is a systematic arrangement of space of grasps. For this purpose, different types of CR-based grasp tasks are overviewed. Also, different types of contact shapes between CRs and objects are classified. Finally, existing CR-based grasp configurations in the CR-related literature are compared and classified into a novel taxonomy through a 3-step methodology. Based on this study, nine major grasp families in the field of CRs are introduced, which include 21 sub-grasp types. Then, the taxonomy is enriched by different analyses of CR-based grasp families. Finally, to study the feasibility of the grasp taxonomy, an experimental case of a small-sized CR is investigated. The second contribution of this thesis is to introduce the formulation of CR-based grasp synthesis. Grasp synthesis is the process of determining the CR configuration and contact points on the target object to acquire suitable grasp properties. In this thesis, a synthesis approach relying on an analytical model of CR-based grasp is proposed. The grasp quality measures, which are key to the grasp selection, are formulated based on grasp and CR Jacobian matrices. The Jacobian matrix for CRs is obtained through piecewise constant-curvature modeling and by Cosserat rod-based models, each providing certain advantages. Besides, to reflect the limited workspace of CRs, a new quantitative grasp quality measure is proposed. Also, two experimental grasp quality measures (i.e., path following error and grasp success rate) are introduced to compare and assess the grasps. Then, the effectiveness of the synthesis algorithms is shown through extensive numerical examples and experiments, using single-segment tendon-driven catheters. Moreover, as a requirement for experimental verifications, an experimental set-up for the automation of CRs is developed in collaboration with other researchers in the lab.</p>

The traditional Rapidly-exploring Random Tree Star (RRT*) suffers from the low path generation efficiency, numerous invalid exploration points, and unsuitability for navigation in unknown dynamic environments. In this article, we propose a dynamic path planning scheme by combining the improved RRT* and the improved dynamic window approach (DWA). For pregenerating an initial path, we use the artificial potential field (APF) method to expand new nodes. The adaptive dynamic step-size is introduced for accelerating the optimal path searching. Moreover, the improved ant colony algorithm is used to perform multiobjective optimization on the generated initial path. When unknown obstacles appear in the path, the improved DWA is developed for obstacle avoidance. Finally, the proposed method is validated by simulation and experiment in both of the static and dynamic environments. In particular, the simulation results show that, compared with some existing methods, our algorithm can generate a higher-quality initial path in the static environment and avoid unknown dynamic obstacles effectively in the dynamic environment. Furthermore, we implement our algorithm in a mobile robot to verify the correctness and effectiveness in the practical scenario.

This study aims to develop a goniometer for capturing images of a real object placed on the goniometer table and regenerating a 3D virtual model of the same object using a series of captured images. The system captures 100 images of the object while the table rotates 360°. By utilizing images taken with a NoIR camera, a 3D virtual model of the real object can be generated. A centralized Raspberry Pi board controls all components of the goniometer. The system includes a control interface that connects to a PC via a Wi-Fi network. Using this interface, the rotation angle of the goniometer table can be adjusted with a minimum step size of 0.9°. The table is connected to a stepper motor, which enables rotation up to 360° with 400 steps per full rotation. As the table rotates, the NoIR camera, connected to the Raspberry Pi, captures images of the object. Additionally, the goniometer includes a rotatable and brightness-adjustable white LED light source. This LED source illuminates the real object on the table and can be controlled via the interface.