952 resultados para Real environment


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To date, the usefulness of stereoscopic visual displays in research on manual interceptive actions has never been examined. In this study, we compared the catching movements of 8 right-handed participants (6 men, 2 women) in a real environment (with suspended balls swinging past the participant, requiring lateral hand movements for interception) with those in a situation in which similar virtual ball trajectories were displayed stereoscopically in a virtual reality system (Cave Automated Virtual Environment [CAVE]; Cruz-Neira, Sandin, DeFranti, Kenyon, & Hart, 1992) with the head fixated. Catching the virtual ball involved grasping a lightweight ball attached to the palm of the hand. The results showed that, compared to real catching, hand movements in the CAVE were (a) initiated later, (b) less accurate, (c) smoother, and (d) aimed more directly at the interception point. Although the latter 3 observations might be attributable to the delayed movement initiation observed in the CAVE, this delayed initiation might have resulted from the use of visual displays. This suggests that stereoscopic visual displays such as present in many virtual reality systems should be used circumspectly in the experimental study of catching and should be used only to address research questions requiring no detailed analysis of the information-based online control of the catching movements.

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This paper describes a study that used video materials and visits to an airport to prepare children on the autism spectrum for travel by plane. Twenty parents and carers took part in the study with children aged from 3 to 16 years. The authors explain that the methods they used were based on Applied Behaviour Analysis (ABA) research; a video modeling technique called Point-Of-View Video-priming and during visits to an airport they used procedures known as Natural Environment Teaching. The findings suggest that using video and preparing children by taking them through what is likely to happen in the real environment when they travel by plane is effective and the authors suggest these strategies could be used to support children with autism with other experiences they need or would like to engage in such as visits to the dentist or hairdressers and access to leisure centres and other public spaces.

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Purpose – The purpose of this paper is to propose a generic model of Integrated Management System of Quality, Environment and Safety (IMS-QES) that can be adapted and progressively to assimilate various Management Systems, of which highlights: ISO 9001 for Quality; ISO 14001 for Environment; OHSAS 18001 for Occupational Health and Safety. Design/methodology/approach – The model was designed in the real environment of a Portuguese Organization and 160 employees were surveyed. The rate response was equal to 86 percent. The conceived model was implemented in a first phase for the integration of Quality, Environment and Safety Management Systems. Findings – Among the main findings of the survey the paper highlights: the elimination of conflicts between individual systems with resources optimization; creation of added value to the business by eliminating several types of wastes; the integrated management of sustainability components in a global market; the improvement of partnerships with suppliers of goods and services; reducing the number of internal and external audits. Originality/value – This case study is one of the first Portuguese empirical researches about IMS-QES and the paper believes that it can be useful in the creation of a Portuguese guideline for integration, namely the Quality Management Systems; Environmental Management Systems and Occupational Health and Safety Management Systems among others.

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The use of virtual reality as tool in the area of spatial cognition raises the question of the quality of learning transfer from a virtual to a real environment. It is first necessary to determine with healthy subjects, the cognitive aids that improve the quality of transfer and the conditions required, especially since virtual reality can be used as effective tool in cognitive rehabilitation. The purpose of this study was to investigate the influence of the exploration mode of virtual environment (Passive vs. Active) according to Route complexity (Simple vs. Complex) on the quality of spatial knowledge transfer in three spatial tasks. Ninety subjects (45 men and 45 women) participated. Spatial learning was evaluated by Wayfinding, sketch-mapping and picture classification tasks in the context of the Bordeaux district. In the Wayfinding task, results indicated that active learning in a Virtual Environment (VE) increased the performances compared to the passive learning condition, irrespective of the route complexity factor. In the Sketch-mapping task, active learning in a VE helped the subjects to transfer their spatial knowledge from the VE to reality, but only when the route was complex. In the Picture classification task, active learning in a VE when the route was complex did not help the subjects to transfer their spatial knowledge. These results are explained in terms of knowledge levels and frame/strategy of reference [SW75, PL81, TH82].

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Accurate characterization of the radio channel in tunnels is of great importance for new signaling and train control communications systems. To model this environment, measurements have been taken at 2.4 GHz in a real environment in Madrid subway. The measurements were carried out with four base station transmitters installed in a 2-km tunnel and using a mobile receiver installed on a standard train. First, with an optimum antenna configuration, all the propagation characteristics of a complex subway environment, including near shadowing, path loss,shadow fading, fast fading, level crossing rate (LCR), and average fade duration (AFD), have been measured and computed. Thereafter, comparisons of propagation characteristics in a double-track tunnel (9.8-m width) and a single-track tunnel (4.8-m width) have been made. Finally, all the measurement results have been shown in a complete table for accurate statistical modeling.

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Abstract The development of cognitive robots needs a strong “sensorial” support which should allow it to perceive the real world for interacting with it properly. Therefore the development of efficient visual-processing software to be equipped in effective artificial agents is a must. In this project we study and develop a visual-processing software that will work as the “eyes” of a cognitive robot. This software performs a three-dimensional mapping of the robot’s environment, providing it with the essential information required to make proper decisions during its navigation. Due to the complexity of this objective we have adopted the Scrum methodology in order to achieve an agile development process, which has allowed us to correct and improve in a fast way the successive versions of the product. The present project is structured in Sprints, which cover the different stages of the software development based on the requirements imposed by the robot and its real necessities. We have initially explored different commercial devices oriented to the acquisition of the required visual information, adopting the Kinect Sensor camera (Microsoft) as the most suitable option. Later on, we have studied the available software to manage the obtained visual information as well as its integration with the robot’s software, choosing the high-level platform Matlab as the common nexus to join the management of the camera, the management of the robot and the implementation of the behavioral algorithms. During the last stages the software has been developed to include the fundamental functionalities required to process the real environment, such as depth representation, segmentation, and clustering. Finally the software has been optimized to exhibit real-time processing and a suitable performance to fulfill the robot’s requirements during its operation in real situations.

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Providing precise positioning services in regional areas to support agriculture, mining, and construction sectors depends on the availability of ground continuously operating GNSS reference stations and communications linking these stations to central computers and users. With the support of CRC for Spatial Information, a more comprehensive review has been completed recently to examine various wired and wireless communication links available for precise positioning services, in particular in the Queensland regional areas. The study covers a wide range of communication technologies that are currently available, including fixed, mobile wireless, and Geo-stationary and or low earth orbiting satellites. These technologies are compared in terms of bandwidth, typical latency, reliability, coverage, and costs. Additionally, some tests were also conducted to determine the performances of different systems in the real environment. Finally, based on user application requirements, the paper discusses the suitability of different communication links.

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本文提出一种聚类引导搜索(cluster guide searching,CGS)的路径规划方法。采用基于最大最小距离的K均值聚类方法对样本进行离线聚类学习,学习结果以相似环境相似决策的知识形式进行存储。路径规划过程中,机器人在线整理环境信息,获得输入空间样本,通过与知识库匹配,检索到最近的类别,然后在该类别内部采用速度优先策略和方向优先策略交替的方式搜索输出空间。若知识不完备导致检索失败,可重启线性规划算法(linear programming,LP)进行在线路径规划,并更新聚类知识库。仿真结果表明该方法是一种有效的路径规划学习方法。

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本文介绍了星球探测机器人视觉系统的标定方法,首先介绍了一种新的从视觉坐标系到车体坐标系的变换方法,随后给出了像机的模型,在像机参数优化过程中将三维重投影误差作为评价函数,利用遗传算法完成寻优过程,以保证估计出的像机参数全局最优。真实环境实验结果表明:该方法具有较高的空间定位精度。

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Currently,one of the important research areas in Spatial updating is the role of external (for instance visual) and internal (for instance proprioceptive or vestibular) information in spatial updating of scene recognition. Our study uses the paradigm of classic spatial updating research and the experimental design of investigation of Burgess(2004),first, we will explore the concrete influence of locomotion on scene recognition in real world; next, we will use virtual reality technology, which can control many spatial learning parameters and exclude the influence of extra irrelevant variables, to explore the influence of pure locomotion without visual cue on scene recognition, and furthermore, we will explore whether the ability of spatial updating can be transferred to new situations in a short period of time and compare the result pattern in real word with that in virtual reality to test the validity of virtual reality technology in spatial updating of scene recognition research. The main results of this paper can be summarized as follows: 1. In real world, we found two effects: the spatial updating effect and the viewpoint dependent effect, this result indicated that the spatial updating effect based on locomotion does not eliminate the viewpoint dependent effect during the scene recognition process in physical environment. 2. In virtual reality environment, we still found two effects: the spatial updating effect and the viewpoint dependent effect, this result showed us that the spatial updating effect based on locomotion does not eliminate the viewpoint dependent effect during the scene recognition process in virtual reality environment either. 3. The spatial updating effect based on locomotion plays double role in scene recognition: When subjects were tested in different viewpoint, spatial updating based on locomotion promoted scene recognition; while subjected were tested in same viewpoint, spatial updating based on locomotion had a negative influence on scene recognition, these results show us that spatial updating based on locomotion is automated and can not be ignored. 4. The ability of spatial updating can be transferred to new situations in a short period of time , and the experiment in the immersed virtual reality environment got the same result pattern with that in the physical environment, suggesting VR technology is a very effective method to do research on spatial updating of the scene recognition studies. 5. This study about scene recognition provides evidence to double system model of spatial updating in the immersed virtual reality environment.

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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

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Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.

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This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented

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This paper shows the impact of the atomic capabilities concept to include control-oriented knowledge of linear control systems in the decisions making structure of physical agents. These agents operate in a real environment managing physical objects (e.g. their physical bodies) in coordinated tasks. This approach is presented using an introspective reasoning approach and control theory based on the specific tasks of passing a ball and executing the offside manoeuvre between physical agents in the robotic soccer testbed. Experimental results and conclusions are presented, emphasising the advantages of our approach that improve the multi-agent performance in cooperative systems