947 resultados para robot teams


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Surveyed 45 therapists who had participated in a family intervention for schizophrenia training program to examine the difficulties they had encountered, their recall of the intervention strategies, and the extent that they thought the approach had become integrated in their everyday work. Between 6 mo and 3 yrs after the family training, Ss reported the number of families they had systematically treated, and the difficulties they had encountered. Allowance of time to undertake the intervention, afterhours scheduling, and illness or holidays presented particular difficulties. Only 4% reported that their knowledge of behavioral techniques was a problem, but in a written test most therapists did not display minimum recall of the material of cognitive therapy, social skills training, or behavioral strategies. The study demonstrated significant problems in disseminating cognitive-behavioral approaches to multidisciplinary settings.

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Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.

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Communication is one team process factor that has received considerable research attention in the team literature. This literature provides equivocal evidence regarding the role of communication in team performance and yet, does not provide any evidence for when communication becomes important for team performance. This research program sought to address this evidence gap by a) testing task complexity and team member diversity (race diversity, gender diversity and work value diversity) as moderators of the team communication — performance relationship; and b) testing a team communication — performance model using established teams across two different task types. The functional perspective was used as the theoretical framework for operationalizing team communication activity. The research program utilised a quasi-experimental research design with participants from a large multi-national information technology company whose Head Office was based in Sydney, Australia. Participants voluntarily completed two team building exercises (a decision making and production task), and completed two online questionnaires. In total, data were collected from 1039 individuals who constituted 203 work teams. Analysis of the data revealed a small number of significant moderation effects, not all in the expected direction. However, an interesting and unexpected finding also emerged from Study One. Large and significant correlations between communication activity ratings were found across tasks, but not within tasks. This finding suggested that teams were displaying very similar profiles of communication on each task, despite the tasks having different communication requirements. Given this finding, Study Two sought to a) determine the relative importance of task versus team effects in explaining variance in team communication measures for established teams; b) determine if established teams had reliable and discernable team communication profiles and if so, c) investigate whether team communication profiles related to task performance. Multi-level modeling and repeated measures analysis of variance (ANOVA) revealed that task type did not have an effect on team communication ratings. However, teams accounted for 24% of the total variance in communication measures. Through cluster analysis, five reliable and distinct team communication profiles were identified. Consistent with the findings of the multi-level analysis and repeated measures ANOVA, teams’ profiles were virtually identical across the decision making and production tasks. A relationship between communication profile and performance was identified for the production task, although not for the decision making task. This research responds to calls in the literature for a better understanding of when communication becomes important for team performance. The moderators tested in this research were not found to have a substantive or reliable effect on the relationship between communication and performance. However, the consistency in team communication activity suggests that established teams can be characterized by their communication profiles and further, that these communication profiles may have implications for team performance. The findings of this research provide theoretical support for the functional perspective in terms of the communication – performance relationship and further support the team development literature as an explanation for the stability in team communication profiles. This research can also assist organizations to better understand the specific types of communication activity and profiles of communication that could offer teams a performance advantage.

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The focus of this study is the phenomenon of teams and teamwork. Currently the Professional Standards of Queensland’s teachers state that teams are critical to teachers’ work. This study uses a phenomenographic approach to investigate science teachers’ conceptions of teams and teamwork in the science departments of fifteen Queensland State secondary schools. The research identifies eight conceptions of teams and teamwork. The research findings suggest that the team represents a collective of science teachers bounded by the Science Department and their current timetabled subject. Collaboration was found in the study to be an activity that occurred between teachers in the same social space. The research recognises a new category of relationship between teachers, designated as ‘ask-and-receive’. The research identifies a lack of teamwork within the science department and the school. There appears to be no teaming with other subject departments. The research findings highlight the non-supportive team and teamwork policies, procedures and structures in the schools and identify the lack of recognition of the specialised skills of science teachers. The implications for the schools and science teachers are considerable, as the current Professional Standards of Education Queensland and the Queensland College of Teachers provide benchmarks of knowledge and practice of teams and teamwork for teachers. The research suggests that the professional standards relating to teams and teamwork cannot be achieved in the present school environment.

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We consider multi-robot systems that include sensor nodes and aerial or ground robots networked together. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We present a sensor network deployment method using autonomous aerial vehicles and describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for repair, to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth). © Springer-Verlag Berlin/Heidelberg 2006.

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The development of autonomous air vehicles can be an expensive research pursuit. To alleviate some of the financial burden of this process, we have constructed a system consisting of four winches each attached to a central pod (the simulated air vehicle) via cables - a cable-array robot. The system is capable of precisely controlling the three dimensional position of the pod allowing effective testing of sensing and control strategies before experimentation on a free-flying vehicle. In this paper, we present a brief overview of the system and provide a practical control strategy for such a system. ©2005 IEEE.

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To navigate successfully in a novel environment a robot needs to be able to Simultaneously Localize And Map (SLAM) its surroundings. The most successful solutions to this problem so far have involved probabilistic algorithms, but there has been much promising work involving systems based on the workings of part of the rodent brain known as the hippocampus. In this paper we present a biologically plausible system called RatSLAM that uses competitive attractor networks to carry out SLAM in a probabilistic manner. The system can effectively perform parameter self-calibration and SLAM in one dimension. Tests in two dimensional environments revealed the inability of the RatSLAM system to maintain multiple pose hypotheses in the face of ambiguous visual input. These results support recent rat experimentation that suggest current competitive attractor models are not a complete solution to the hippocampal modelling problem.

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This paper illustrates the prediction of opponent behaviour in a competitive, highly dynamic, multi-agent and partially observable environment, namely RoboCup small size league robot soccer. The performance is illustrated in the context of the highly successful robot soccer team, the RoboRoos. The project is broken into three tasks; classification of behaviours, modelling and prediction of behaviours and integration of the predictions into the existing planning system. A probabilistic approach is taken to dealing with the uncertainty in the observations and with representing the uncertainty in the prediction of the behaviours. Results are shown for a classification system using a Naïve Bayesian Network that determines the opponent’s current behaviour. These results are compared to an expert designed fuzzy behaviour classification system. The paper illustrates how the modelling system will use the information from behaviour classification to produce probability distributions that model the manner with which the opponents perform their behaviours. These probability distributions are show to match well with the existing multi-agent planning system (MAPS) that forms the core of the RoboRoos system.

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This paper describes experiments conducted in order to simultaneously tune 15 joints of a humanoid robot. Two Genetic Algorithm (GA) based tuning methods were developed and compared against a hand-tuned solution. The system was tuned in order to minimise tracking error while at the same time achieve smooth joint motion. Joint smoothness is crucial for the accurate calculation of online ZMP estimation, a prerequisite for a closedloop dynamically stable humanoid walking gait. Results in both simulation and on a real robot are presented, demonstrating the superior smoothness performance of the GA based methods.

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This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.

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This paper describes the real time global vision system for the robot soccer team the RoboRoos. It has a highly optimised pipeline that includes thresholding, segmenting, colour normalising, object recognition and perspective and lens correction. It has a fast ‘paint’ colour calibration system that can calibrate in any face of the YUV or HSI cube. It also autonomously selects both an appropriate camera gain and colour gains robot regions across the field to achieve colour uniformity. Camera geometry calibration is performed automatically from selection of keypoints on the field. The system achieves a position accuracy of better than 15mm over a 4m × 5.5m field, and orientation accuracy to within 1°. It processes 614 × 480 pixels at 60Hz on a 2.0GHz Pentium 4 microprocessor.

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This paper describes an autonomous docking system and web interface that allows long-term unaided use of a sophisticated robot by untrained web users. These systems have been applied to the biologically inspired RatSLAM system as a foundation for testing both its long-term stability and its practicality. While docking and web interface systems already exist, this system allows for a significantly larger margin of error in docking accuracy due to the mechanical design, thereby increasing robustness against navigational errors. Also a standard vision sensor is used for both long-range and short-range docking, compared to the many systems that require both omni-directional cameras and high resolution Laser range finders for navigation. The web interface has been designed to accommodate the significant delays experienced on the Internet, and to facilitate the non- Cartesian operation of the RatSLAM system.