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Proper platform pose is important for the mobile manipulator to accomplish dexterous manipulation tasks efficiently and safely, and the evaluation criterion to qualify manipulation performance is critical to support the pose decision process. This paper aims to present a comprehensive index to evaluate the manipulator’s operation performance from various aspects.

In this research, a criterion called hybrid manipulability (HM) is proposed to assess the performance of the manipulator’s operation, considering crucial factors such as joint limits, obstacle avoidance and stability. The determination of the optimal platform pose is achieved by selecting the pose that maximizes the HM within the feasible inverse reachability map associated with the target object.

A self-built mobile manipulator is adopted as the experimental platform, and the feasibility of the proposed method is experimentally verified in the context of object-grasping tasks both in simulation and practice.

The proposed HM extends upon the conventional notion of manipulability by incorporating additional factors, including the manipulator’s joint limits, the obstacle avoidance situation during the operation and the manipulation stability when grasping the target object. The manipulator can achieve enhanced stability during grasping when positioned in the pose determined by the HM.

The capability to perform dexterous operations in an autonomous manner would greatly enhance the productivity of robotic operations. In this paper, we present a new methodology for vision‐based grasping of objects or parts using a three‐finger hand as a gripper of a robotic manipulator.

The hand employed in our work, called SARAH, was designed for robotic operations on the space station, however, the main steps of our procedure can be applied for tasks in a manufacturing environment. Our methodology involves two principal stages: automatic synthesis of grasps for planar and revolute objects with SARAH and vision‐based pose estimation of the object to be grasped. For both stages, we assume that a model of the object is available off‐line.

In the paper, numerical results are presented for grasp synthesis of several objects with SARAH to demonstrate the feasibility and optimality of the synthesized grasps. Experimental results are also obtained with SARAH as the end‐effector of a seven‐degree‐of‐freedom robotic arm, demonstrating the feasibility of the integrated vision‐based grasping.

The methodology described in the paper, although represents a substantial step towards automated grasping with a robotic manipulator, still requires some decision making from the user. Further work can improve the pose identification aspects of the algorithm to make them more robust and free of human intervention. As well, the grasp synthesis procedure can be expanded to handle more complex and possibly moving objects, as well as to allow for different grasp types than those considered here.

The work demonstrates feasibility of autonomous grasp execution in industrial setting by using a three‐finger hand as a robotic gripper.

The results presented in the paper demonstrate the feasibility of synthesising optimised grasps which take into account the kinematics of the gripper. We also demonstrate a real implementation of vision‐based grasping by using a robotic manipulator with a three‐finger hand.

Aims to develop a robotic platform to autonomously track a moving object

This robotic platform, based on a modular system known as SafeBot, uses two sensors: a visual CCD camera and a laser‐based range sensor. The rigidly mounted camera tracks an object in front of the platform and generates appropriate drive commands to keep the object in view, even if the object itself moves. The range sensor detects other objects as the platform moves to provide real‐time obstacle avoidance while continuously tracking the original object.

The current approach successfully tracks an object, particularly a human subject, and avoids reasonably sized obstacles, but on‐board processing limitations restrict the speed of the object to approximately 5 km/h.

The core technology – a moving object tracked by a mobile robot with real‐time obstacle avoidance – is an integrated system comprising object tracking on a mobile platform and real‐time obstacle avoidance with robotic control. This system is applicable to a variety of automated applications such as inventory management, industrial palette distribution, and intruder surveillance.

The purpose of this paper is to propose a web‐based tool that enables the development and provision of learning designs and its reuse and re‐contextualization as generative learning objects, aimed at developing educational materials.

The use of learning objects can facilitate the process of production and delivering of educational material and their reuse and re‐contextualization in different scenarios – such process is due to the current development stage of information and communication technologies (ICTs), which allow easy access to products and services related to them. ICTs combined with instructional design theories, lead to the emergence of new generations of distance learning, which add educational content to web‐based services. From this combination rises a hybrid mode of education, which combines tools for face‐to‐face and distance learning (blended learning).

The use of the web as a platform for production and management of learning objects comes as a solution for storage and sharing. The utilization of objects is justified when its reusability is facilitated. This gives rise to possibilities in a client‐server environment, where information is centralized and available anywhere in the network.

The combination of ICT and instructional design theories has potential and could result in hybrids which are yet to be fully understood and explored. This can enhance blended learning provision.

The paper presents a tool in which the learning designs work as structures built on XML, based on concept maps, which act as an interaction layer between the learning objects, organizing the content to be available.

An object oriented finite element model is presented. The main advantage of this model over conventional systems is that, the additional code required for adding elements to the finite element library is minimal. The powerful mechanisms provided by object oriented systems facilitate this. These mechanisms enable re‐use of existing code, and allow the programmer to leave certain operations to the computer, which, without object oriented techniques, would not have been possible. In the above model, the finite elements are represented in the form of a hierarchical tree by which it is possible to develop elements by programming only the differences from existing elements. Suitable object oriented designs have been developed for representing mathematical entities like differential operators and shape functions, with a view to automating the process of development of element properties, so that, the element developer needs to specify just the minimum details, leaving most of the operations to the computer. Some of the concepts in object oriented programming are explained in detail, with the examples used in the above model.

To provide original knowledge for graduate students, research workers and specialists in ability maintenance system of engineering systems in range of improving their diagnostic susceptibility in order to improve of credibility of worked out diagnosis, genesis and forecast.

In this work are methodological guidelines to realize a process of improving of diagnostic susceptibility of engineering systems, which can be approached as an automatics system. It can be hydraulic, pneumatic and fuel systems, oil and gas pipelines, etc.

It was noticed and next theoretically and experimentally confirmed that signals of weak interactions, which can excite between a tested object (hydraulic system) and a adjoined testing object (a corrector), are an additional piece of diagnostic information. This information allows for an increase of reliability of diagnosis, which is working out.

The signals of weak interactions can arise, when a tested object can be approached as an automatic control system (ACS), in which can be distinguished a controlled system (e.g. installation) and a control unit (e.g. pump). Experimental research was realized on a physical model of the airplane hydraulic installation. Other object requires similar investigations.

The development of functional (parametric and signal‐based) diagnosing methods. The proposition of “signal‐based diagnostics” based on the indicators of quality of course signal. These indicators result from the principles of the automatics, and from parametric diagnostics, resulting from the principles of the static and dynamic identification of diagnosing objects.

The proposition of receiving diagnostic information, also during observation of phenomena, which occur in a feedback path of automatics systems, in which operates a specially adjoined corrector (a testing object). Such approach allows by means of change of corrector's parameters to determine optionally a required sensitivity of measuring system, and to control a set value into the corrector, which is an output signal in the occurring in the past.

Plant configuration management systems address all phases of the plant’s life cycle, from engineering design, re‐design, maintenance, to operations. However, as yet little research has been reported on plant configuration management information systems analysis. During the past decade, the object‐oriented approach has received much attention in information systems development. This paper describes an object structure for plant configuration management systems analysis. Three major aspects of configuration management (maintenance, re‐design change, and business process) and fundamental types of objects engaged in configuration management are described. The association between these objects is then built through identifying the messages between the objects. Practical application of this framework shows that it is useful for the analysis and design of a plant configuration management information system.

This paper aims to help archaeologists, museums’ curators and technicians in understanding the principle of using the photogrammetry and 3D scanner for the museum archaeological objects in a practical way by presenting specific examples for both methods. Another purpose is to evaluate the performance offered by the photogrammetry and the three-dimensional (3D) scanner device, with the aim of providing a suitable solution to the different shapes and sizes of the archaeological objects.

The author used the camera Canon EOS 1300 D for photographing and Einscan Pro 2X Plus as a 3D scanning device for several years on different kinds of objects made of various materials, including ceramic, stone, glass and metal.

This paper showed that both approaches create 3D models with high resolution in easy and different ways.

Handling objects and preparing them for photographing or scanning has involved a number of caveats and challenges regarding the risk of damage that the author had to bear in mind.

This paper is completely based on the author’s personal experiences of creating 3D image of various objects in the project of Documentation of Objects in the Jordanian Archaeological Museums.

One of the main goals of vision systems is to recognize objects in real world to perform appropriate actions. This implies the ability of handling objects and, moreover, to know the relations between these objects and their environment in what we call scenes. Most of the time, navigation in unknown environments is difficult due to a lack of easily identifiable landmarks. Hence, in this work, some geometric features to identify objects are considered. Firstly, a Markov random field segmentation approach is implemented. Then, the key factor for the recognition is the calculation of the so‐called distance histograms, which relate the distances between the border points to the mass center for each object in a scene.

This work, first discusses the features to be analyzed in order to create a reliable database for a proper recognition of the objects in a scene. Then, a robust classification system is designed and finally some experiments are completed to show that the recognition system can be utilized in a real‐world operation.

The results of the experiments show that including this distance information improves significantly the final classification process.

This paper describes an object recognition scheme, where a set of histograms is included to the features vector. As is shown, the incorporation of this feature improves the robustness of the system and the recognition rate.

In the community of visual tracking or object tracking, discriminatively learned correlation filter (DCF) has gained more importance. When it comes to speed, DCF gives the best performance. The purpose of this study is to anticipate the object visually. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique. Features like HOG and Harris are used for the process of feature extraction. The authors’ proposed method will give the best results when compared with other existing methods.

The visual tracking of many real-world applications such as robotics, smart monitoring systems, independent driving and human-computer interactions are a major and current research problem in the field of computer vision. This refers to the automated trajectory prediction of an arbitrary target object, often given in the first frame in a bounding box while moving about in successive video frames. In the community of visual tracking or object tracking, DCF has gained more importance. Discriminative trackers strive to train a classifier that differentiates the target item from the background. The fundamental concept is to train a correlation filter that creates high responses around the target and low responses elsewhere. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique. Features like HOG and Harris are used for the process of feature extraction. Through experimental analysis, the authors have evaluated several performance assessment metrics such as accuracy, precision, F-measure and specificity. The authors’ proposed method will give the best results when compared with other existing methods.

This process involved DCF which gained more importance. When it comes to speed, DCF gives the best performance. The main objective of this study is to anticipate the object visually. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique for tracking the objects and these results will be used for identifying the action of the object.

The main theme exists in the process is to identify the tracking motion of the object by using convolution regression with varied features. This method proves that it will provide better results when compared to state of art methods.