936 resultados para networked robotics


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The knowledge economy relies on the diffusion and use of knowledge as well as its creation (Houghton and Sheenan, 2000). The future success of economic activity will depend on the capacity of organisations to transform by increasing their flexibility. In particular, this transformation is dependant on a decentralised, networked and multi-skilled workforce. To help organisations transition, new strategies and structures for education are required. Education systems need to concentrate less on specialist skills and more on the development of people with broad-based problem solving skills that are adaptable, with social and inter-personal communication skills necessary for networking and communication. This paper presents the findings of a ‘Knowledge Economy Market Development Mapping Study’ conducted to identify the value of design education programs from primary through to tertiary level in Queensland, Australia. The relationship of these programs to the development of the capacities mentioned above is explored. The study includes the collection of qualitative and quantitative data consisting of a literature review, focus groups and survey. Recommendations for the future development of design education programs in Queensland, Australia are proposed, and future research opportunities are presented and discussed.

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The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

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This paper explores the design of virtual and physical learning spaces developed for students of drama and theatre studies. What can we learn from the traditional drama workshop that will inform the design of drama and theatre spaces created in technology-mediated learning environments? The authors examine four examples of spaces created for online, distance and on-campus students and discuss the relationship between the choice of technology, the learning and teaching methods, and the outcomes for student engagement. Combining insights from two previous action research projects, the discussion focuses on the physical space used for contemporary drama workshops, supplemented by Web 2.0 technologies; a modular online theatre studies course; the blogging space of students creating a group devised play; and the open and immersive world of Second Life, where students explore 3D simulations of historical theatre sites. The authors argue that the drama workshop can be used as inspiration for the design of successful online classrooms. This is achieved by focusing on students’ contributions to the learning as individuals and group members, the aesthetics and mise-en-scene of the learning space, and the role of mobile and networked technologies. Students in this environment increase their capacity to become co-creators of knowledge and to achieve creative outcomes. The drama workshop space in its physical and virtual forms is seen as a model for classrooms in other disciplines, where dynamic, creative and collaborative spaces are required.

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This paper presents a novel evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles (UAVs) with tactical and kinematic constraints. A genetic algorithm (GA) is modified and extended for path planning. Two GAs are seeded at the initial and final positions with a common objective to minimise their distance apart under given UAV constraints. This is accomplished by the synchronous optimisation of subsequent control vectors. The proposed evolutionary computation approach is called synchronous genetic algorithm (SGA). The sequence of control vectors generated by the SGA constitutes to a near-optimal path plan. The resulting path plan exhibits no discontinuity when transitioning from curve to straight trajectories. Experiments and results show that the paths generated by the SGA are within 2% of the optimal solution. Such a path planner when implemented on a hardware accelerator, such as field programmable gate array chips, can be used in the UAV as on-board replanner, as well as in ground station systems for assisting in high precision planning and modelling of mission scenarios.

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Deploying networked control systems (NCSs) over wireless networks is becoming more and more popular. However, the widely-used transport layer protocols, Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), are not designed for real-time applications. Therefore, they may not be suitable for many NCS application scenarios because of their limitations on reliability and/or delay performance, which real-control systems concern. Considering a typical type of NCSs with periodic and sporadic real-time traffic, this paper proposes a highly reliable transport layer protocol featuring a packet loss-sensitive retransmission mechanism and a prioritized transmission mechanism. The packet loss-sensitive retransmission mechanism is designed to improve the reliability of all traffic flows. And the prioritized transmission mechanism offers differentiated services for periodic and sporadic flows. Simulation results show that the proposed protocol has better reliability than UDP and improved delay performance than TCP over wireless networks, particularly when channel errors and congestions occur.

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One aspect of quality education in the 21st century is the availability of digital resources in schools. Many developing countries need to build this capability – not just in terms of technology but teacher capability as well. One of the ways to achieve such capacity is through knowledge sharing between teachers and educators in developed and developing countries. Over time such collaboration can have a lasting impact on all participants on both sides of the digital divide. This paper reports on how such collaboration can occur. It focuses on the initial stages of a long-term initiative where our primary objective is to develop models, which demonstrate how we (in developed countries) can engage productively and meaningfully with schools in developing countries to build their ICT capacity. As part of this initiative, we introduced laptops and LEGO robotics tool kits to a rural primary school in Fiji. We developed ICT activities that aligned with the curriculum in a number of subjects. In addition, we worked with the teachers over two weeks to build their expertise.

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Within contemporary performance arenas young people are fast becoming part of the vanguard of contemporary performance. Performativity, convergence and openness of form are key animating concepts in the landscape of Theatre for Young People (TYP). To ignore what is taking place in the making of performance for and by young people is to ignore the new possibilities in meaning-making and theatrical form. This thesis investigates the contemporary practice within the field of Theatre for Young People. Pivotal to the study are three hallmarks of contemporary performance – shifting notions of performativity; convergence articulated in the use of technology and theatrical genres; and Umberto Eco’s realisation of openness in form and authorship. The thesis draws from theatre and performance studies, globalisation theory and youth studies. Using interviews of Theatre for Young People practitioners and observation of thirty-nine performances, this thesis argues that young people and Theatre for Young People companies are among the leaders of a paradigm shift in developing and delivering performance works. In this period of rapid technological change young people are embracing and manipulating technology (sound, image, music) to represent whom they are and what they want to say. Positioned as ‘cultural catalysts’ (McRobbie, 1999), ‘the new pioneers’ (Mackay, 1993) and ‘first navigators’ (Rushkoff, 1996) young people are using mediatised culture and digital technologies with ease, placing them at the forefront of a shift in cultural production. The processes of deterritorialisation allows for the synthesis of new cultural and performance genres by fragmenting and hybridising traditional cultural categories and forms including the use of new media technologies. Almost half of all TYP performances now incorporate the technologies of reproduction. The relationship between live and mediatised forms, the visceral and the virtual is allowing young people to navigate and make meaning of cultural codes and cultural forms as well as to engage in an open dialogue with their audiences. This thesis examines the way young people are using elements of deterritorialisation to become producers of new performance genres. The thesis considers the contemporary situation in relation to issues of performance making and performance delivery within a global, networked and technology-driven society.

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This paper is concerned with the unsupervised learning of object representations by fusing visual and motor information. The problem is posed for a mobile robot that develops its representations as it incrementally gathers data. The scenario is problematic as the robot only has limited information at each time step with which it must generate and update its representations. Object representations are refined as multiple instances of sensory data are presented; however, it is uncertain whether two data instances are synonymous with the same object. This process can easily diverge from stability. The premise of the presented work is that a robot's motor information instigates successful generation of visual representations. An understanding of self-motion enables a prediction to be made before performing an action, resulting in a stronger belief of data association. The system is implemented as a data-driven partially observable semi-Markov decision process. Object representations are formed as the process's hidden states and are coordinated with motor commands through state transitions. Experiments show the prediction process is essential in enabling the unsupervised learning method to converge to a solution - improving precision and recall over using sensory data alone.

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The challenge of persistent appearance-based navigation and mapping is to develop an autonomous robotic vision system that can simultaneously localize, map and navigate over the lifetime of the robot. However, the computation time and memory requirements of current appearance-based methods typically scale not only with the size of the environment but also with the operation time of the platform; also, repeated revisits to locations will develop multiple competing representations which reduce recall performance. In this paper we present a solution to the persistent localization, mapping and global path planning problem in the context of a delivery robot in an office environment over a one-week period. Using a graphical appearance-based SLAM algorithm, CAT-Graph, we demonstrate constant time and memory loop closure detection with minimal degradation during repeated revisits to locations, along with topological path planning that improves over time without using a global metric representation. We compare the localization performance of CAT-Graph to openFABMAP, an appearance-only SLAM algorithm, and the path planning performance to occupancy-grid based metric SLAM. We discuss the limitations of the algorithm with regard to environment change over time and illustrate how the topological graph representation can be coupled with local movement behaviors for persistent autonomous robot navigation.

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Ocean gliders constitute an important advance in the highly demanding ocean monitoring scenario. Their effciency, endurance and increasing robustness make these vehicles an ideal observing platform for many long term oceanographic applications. However, they have proved to be also useful in the opportunis-tic short term characterization of dynamic structures. Among these, mesoscale eddies are of particular interest due to the relevance they have in many oceano-graphic processes.

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Our everyday environment is full of text but this rich source of information remains largely inaccessible to mobile robots. In this paper we describe an active text spotting system that uses a small number of wide angle views to locate putative text in the environment and then foveates and zooms onto that text in order to improve the reliability of text recognition. We present extensive experimental results obtained with a pan/tilt/zoom camera and a ROS-based mobile robot operating in an indoor environment.

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RatSLAM is a navigation system based on the neural processes underlying navigation in the rodent brain, capable of operating with low resolution monocular image data. Seminal experiments using RatSLAM include mapping an entire suburb with a web camera and a long term robot delivery trial. This paper describes OpenRatSLAM, an open-source version of RatSLAM with bindings to the Robot Operating System framework to leverage advantages such as robot and sensor abstraction, networking, data playback, and visualization. OpenRatSLAM comprises connected ROS nodes to represent RatSLAM’s pose cells, experience map, and local view cells, as well as a fourth node that provides visual odometry estimates. The nodes are described with reference to the RatSLAM model and salient details of the ROS implementation such as topics, messages, parameters, class diagrams, sequence diagrams, and parameter tuning strategies. The performance of the system is demonstrated on three publicly available open-source datasets.

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This paper introduces a high-speed, 100Hz, visionbased state estimator that is suitable for quadrotor control in close quarters manoeuvring applications. We describe the hardware and algorithms for estimating the state of the quadrotor. Experimental results for position, velocity and yaw angle estimators are presented and compared with motion capture data. Quantitative performance comparison with state-of-the-art achievements are also presented.

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Service robots that operate in human environments will accomplish tasks most efficiently and least disruptively if they have the capability to mimic and understand the motion patterns of the people in their workspace. This work demonstrates how a robot can create a humancentric navigational map online, and that this map re ects changes in the environment that trigger altered motion patterns of people. An RGBD sensor mounted on the robot is used to detect and track people moving through the environment. The trajectories are clustered online and organised into a tree-like probabilistic data structure which can be used to detect anomalous trajectories. A costmap is reverse engineered from the clustered trajectories that can then inform the robot's onboard planning process. Results show that the resultant paths taken by the robot mimic expected human behaviour and can allow the robot to respond to altered human motion behaviours in the environment.

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Changing environments present a number of challenges to mobile robots, one of the most significant being mapping and localisation. This problem is particularly significant in vision-based systems where illumination and weather changes can cause feature-based techniques to fail. In many applications only sections of an environment undergo extreme perceptual change. Some range-based sensor mapping approaches exploit this property by combining occasional place recognition with the assumption that odometry is accurate over short periods of time. In this paper, we develop this idea in the visual domain, by using occasional vision-driven loop closures to infer loop closures in nearby locations where visual recognition is difficult due to extreme change. We demonstrate successful map creation in an environment in which change is significant but constrained to one area, where both the vanilla CAT-Graph and a Sum of Absolute Differences matcher fails, use the described techniques to link dissimilar images from matching locations, and test the robustness of the system against false inferences.