993 resultados para autonomous art
Resumo:
This paper explores models of teaching and learning music composition in higher education. It analyses the pedagogical approaches apparent in the literature on teaching and learning composition in schools and universities, and introduces a teaching model as: learning from the masters; mastery of techniques; exploring ideas; and developing voice. It then presents a learning model developed from a qualitative study into students’ experiences of learning composition at university as: craft, process and art. The relationship between the students’ experiences and the pedagogical model is examined. Finally, the implications for composition curricula in higher education are presented.
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A number of advanced driver assistance systems (ADAS) are currently being released on the market, providing safety functions to the drivers such as collision avoidance, adaptive cruise control or enhanced night-vision. These systems however are inherently limited by their sensory range: they cannot gather information from outside this range, also called their “perceptive horizon”. Cooperative systems are a developing research avenue that aims at providing extended safety and comfort functionalities by introducing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications to the road actors. This paper presents the problematic of cooperative systems, their advantages and contributions to road safety and exposes some limitations related to market penetration, sensors accuracy and communications scalability. It explains the issues of how to implement extended perception, a central contribution of cooperative systems. The initial steps of an evaluation of data fusion architectures for extended perception are exposed.
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The purpose of this paper is to highlight important issues in the study of dysfunctional customer behavior and to provide a research agenda to inspire, guide, and enthuse. Through a critical evaluation of existing research, the aim is to highlight key issues and to present potentially worthy avenues for future study.
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Lumia: art/light/motion is an exciting new media exhibition presented by State Library of Queensland in partnership with Queensland-based Kuuki collective artists Priscilla Bracks and Gavin Sade. The exhibition explored contemporary life and encourages thought about the future through an extraordinary collection of hand-crafted and interactive electronic creatures and installations. The beautifully crafted new media artworks in Lumia: art/light/motion combine the bespoke with art and technology to create strange but intriguing objects. Lumia invited audiences to play, learn and then ponder the way we live and the environmental and social implications of our choices.
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This article examines the moment of exchange between artist, audience and culture in Live Art. Drawing on historical and contemporary examples, including examples from the Exist in 08 Live Art Event in Brisbane, Australia, in October 2008, it argues that Live Art - be it body art, activist art, site-specific performance, or other sorts of performative intervention in the public sphere - is characterised by a common set of claims about activating audiences, asking them to reflect on cultural norms challenged in the work. Live Art presents risky actions, in a context that blurs the boundaries between art and reality, to position audients as ‘witnesses’ who are personally implicated in, and responsible for, the actions unfolding before them. This article problematises assumptions about the way the uncertainties embedded in the Live Art encounter contribute to its deconstructive agenda. It uses the ethical theory of Emmanuel Levinas, Hans-Thies Lehmann and Dwight Conquergood to examine the mechanics of reductive, culturally-recuperative readings that can limit the efficacy of the Live Art encounter. It argues that, though ‘witnessing’ in Live Art depends on a relation to the real - real people, taking real risks, in real places - if it fails to foreground theatrical frame it is difficult for audients to develop the dual consciousness of the content, and their complicity in that content, that is the starting point for reflexivity, and response-ability, in the ethical encounter.
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A small collection of creative works developed to acompany some of the artistic images developed by visual artist Dr Pamela Croft for the Yeppoon Public Art Project in 2000.
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Confucius was and still is one of the most eminent Chinese philosophers. Such is the importance of Confucius’s teachings; it had influenced all aspects of social life in Chinese societies. In the post-Enron, post-Worldcom, and post-Global Financial Crisis era there are raising doubts in the mantra of the so-called conventional wisdom about law and economic order. Whilst many recent publications offered solutions to those problems like advocating for more laws, rules or reforms in regulatory institutions to enhance the regulation of corporate governance. What Confucius advocated was a non-legal, social mode of regulation based on moral ideals that should be embedded into the minds of every person. Whilst this is an ancient concept from primitive societies, its relevance and merits could be seen in modern Chinese societies like Hong Kong. In essence, Confucian principles of governance build on relational and paternalistic order based on moral ideals.
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Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is becoming more prevalent. Intelligent planning is required to maneuver a vehicle to high-valued locations to perform data collection. In this paper, we present algorithms that determine paths for AUVs to track evolving features of interest in the ocean by considering the output of predictive ocean models. While traversing the computed path, the vehicle provides near-real-time, in situ measurements back to the model, with the intent to increase the skill of future predictions in the local region. The results presented here extend prelim- inary developments of the path planning portion of an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. This extension is the incorporation of multiple vehicles to track the centroid and the boundary of the extent of a feature of interest. Similar algorithms to those presented here are under development to consider additional locations for multiple types of features. The primary focus here is on algorithm development utilizing model predictions to assist in solving the motion planning problem of steering an AUV to high-valued locations, with respect to the data desired. We discuss the design technique to generate the paths, present simulation results and provide experimental data from field deployments for tracking dynamic features by use of an AUV in the Southern California coastal ocean.
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Autonomous underwater gliders are robust and widely-used ocean sampling platforms that are characterized by their endurance, and are one of the best approaches to gather subsurface data at the appropriate spatial resolution to advance our knowledge of the ocean environment. Gliders generally do not employ sophisticated sensors for underwater localization, but instead dead-reckon between set waypoints. Thus, these vehicles are subject to large positional errors between prescribed and actual surfacing locations. Here, we investigate the implementation of a large-scale, regional ocean model into the trajectory design for autonomous gliders to improve their navigational accuracy. We compute the dead-reckoning error for our Slocum gliders, and compare this to the average positional error recorded from multiple deployments conducted over the past year. We then compare trajectory plans computed on-board the vehicle during recent deployments to our prediction-based trajectory plans for 140 surfacing occurrences.
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Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.
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In this paper, we present a control strategy design technique for an autonomous underwater vehicle based on solutions to the motion planning problem derived from differential geometric methods. The motion planning problem is motivated by the practical application of surveying the hull of a ship for implications of harbor and port security. In recent years, engineers and researchers have been collaborating on automating ship hull inspections by employing autonomous vehicles. Despite the progresses made, human intervention is still necessary at this stage. To increase the functionality of these autonomous systems, we focus on developing model-based control strategies for the survey missions around challenging regions, such as the bulbous bow region of a ship. Recent advances in differential geometry have given rise to the field of geometric control theory. This has proven to be an effective framework for control strategy design for mechanical systems, and has recently been extended to applications for underwater vehicles. Advantages of geometric control theory include the exploitation of symmetries and nonlinearities inherent to the system. Here, we examine the posed inspection problem from a path planning viewpoint, applying recently developed techniques from the field of differential geometric control theory to design the control strategies that steer the vehicle along the prescribed path. Three potential scenarios for surveying a ship?s bulbous bow region are motivated for path planning applications. For each scenario, we compute the control strategy and implement it onto a test-bed vehicle. Experimental results are analyzed and compared with theoretical predictions.
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An autonomous underwater vehicle (AUV) is expected to operate in an ocean in the presence of poorly known disturbance forces and moments. The uncertainties of the environment makes it difficult to apply open-loop control scheme for the motion planning of the vehicle. The objective of this paper is to develop a robust feedback trajectory tracking control scheme for an AUV that can track a prescribed trajectory amidst such disturbances. We solve a general problem of feedback trajectory tracking of an AUV in SE(3). The feedback control scheme is derived using Lyapunov-type analysis. The results obtained from numerical simulations confirm the asymptotic tracking properties of the feedback control law. We apply the feedback control scheme to different mission scenarios, with the disturbances being initial errors in the state of the AUV.
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Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.
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The main focus of this paper is on the motion planning problem for an under-actuated, submerged, Omni-directional autonomous vehicle. Underactuation is extremely important to consider in ocean research and exploration. Battery failure, actuator malfunction and electronic shorts are a few reasons that may cause the vehicle to lose direct control of one or more degrees-of-freedom. Underactuation is also critical to understand when designing vehicles for specific tasks, such as torpedo-shaped vehicles. An under-actuated vehicle is less controllable, and hence, the motion planning problem is more difficult. Here, we present techniques based on geometric control to provide solutions to the under-actuated motion planning problem for a submerged underwater vehicle. Our results are validated with experiments.