498 resultados para motor planning
Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks
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10 page document containing expert assessment of shortcomings of Western Australian State Planning Policy SPP3.7- Planning for Bushfire Risk Management. Document produced on behalf of QUT and submitted to and published by the WAPC as part of their public consultation process for their draft policy.
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Every university in Australia has a set of policies that guide the institution in its educational practices, however, the policies are often developed in isolation to each other. Now imagine a space where policies are evidence-based, refined annually, cohesively interrelated, and meet stakeholders’ needs. Is this happenstance or the result of good planning? Culturally, Queensland University of Technology (QUT) is a risk-averse institution that takes pride in its financial solvency and is always keen to know “how are we going?” With a twenty-year history of annual reporting that assures the quality of course performance through multiple lines of evidence, QUT’s Learning and Teaching Unit went one step further and strategically aligned a suite of policies that take into consideration the needs of their stakeholders, collaborate with other areas across the institution and use multiple lines of evidence to inform curriculum decision-making. In QUT’s experience, strategic planning can lead to policy that is designed to meet stakeholders’ needs, not manage them; where decision-making is supported by evidence, not rhetoric; where all feedback is incorporated, not ignored; and where policies are cohesively interrelated, not isolated. While many may call this ‘policy nirvana’, QUT has positioned itself to demonstrate good educational practice through Reframe, its evaluation framework. In this case, best practice was achieved through the application of a theory of change and a design-led logic model that allows for transition to other institutions with different cultural specificity. The evaluation approach follows Seldin’s (2003) notion to offer depth and breadth to the evaluation framework along with Berk’s (2005) concept of multiple lines of evidence. In summary, this paper offers university executives, academics, planning and quality staff an opportunity to understand the critical steps that lead to strategic planning and design of evidence-based educational policy that positions a university for best practice in learning and teaching.
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This paper presents an extension to the Rapidly-exploring Random Tree (RRT) algorithm applied to autonomous, drifting underwater vehicles. The proposed algorithm is able to plan paths that guarantee convergence in the presence of time-varying ocean dynamics. The method utilizes 4-Dimensional, ocean model prediction data as an evolving basis for expanding the tree from the start location to the goal. The performance of the proposed method is validated through Monte-Carlo simulations. Results illustrate the importance of the temporal variance in path execution, and demonstrate the convergence guarantee of the proposed methods.
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There is a need for systems which can autonomously perform coverage tasks on large outdoor areas. Unfortunately, the state-of-the-art is to use GPS based localization, which is not suitable for precise operations near trees and other obstructions. In this paper we present a robotic platform for autonomous coverage tasks. The system architecture integrates laser based localization and mapping using the Atlas Framework with Rapidly-Exploring Random Trees path planning and Virtual Force Field obstacle avoidance. We demonstrate the performance of the system in simulation as well as with real world experiments.
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This invention concerns the control of rotating excavation machinery, for instance to avoid collisions with obstacles. In a first aspect the invention is a control system for autonomous path planning in excavation machinery, comprising: A map generation subsystem to receive data from an array of disparate and complementary sensors to generate a 3-Dimensional digital terrain and obstacle map referenced to a coordinate frame related to the machine's geometry, during normal operation of the machine. An obstacle detection subsystem to find and identify obstacles in the digital terrain and obstacle map, and then to refine the map by identifying exclusion zones that are within reach of the machine during operation. A collision detection subsystem that uses knowledge of the machine's position and movements, as well as the digital terrain and obstacle map, to identify and predict possible collisions with itself or other obstacles, and then uses a forward motion planner to predict collisions in a planned path. And, a path planning subsystem that uses information from the other subsystems to vary planned paths to avoid obstacles and collisions. In other aspects the invention is excavation machinery including the control system; a method for control of excavation machinery; and firmware and software versions of the control system.
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Problem, research strategy and findings: On January 10, 2011, the town of Grantham, Queensland (Australia), was inundated with a flash flood in which 12 of the town's 370 residents drowned. The overall damage bill in Queensland was AUD∃2.38 billion (USD∃2.4 billion) with 35 deaths, and more than three-quarters of the state was declared a flood disaster zone. In this study, we focus on the unusual and even rare decision to relocate Grantham in March 2011. The Lockyer Valley Regional Council (LVRC) acquired a 377-hectare (932-acre) site to enable a voluntary swap of equivalent-sized lots. In addition, planning regulations were set aside to streamline the relocation of a portion of the town. We review the natural hazard literature as it relates to community relocation, state and local government documents related to Grantham, and reports and newspaper articles related to the flood. We also analyze data from interviews with key stakeholders. We document the process of community relocation, assess the relocation process in Grantham against best practice, examine whether the process of community relocation can be upscaled and if the Grantham relocation is an example of good planning or good politics. Takeaway for practice: Our study reveals two key messages for practice. Community relocation (albeit a small one) is possible, and the process can be done quickly; some Grantham residents moved into their new, relocated homes in December 2012, just 11 months after the flood. Moreover, the role of existing planning regulations can be a hindrance to quick action; political leadership, particularly at the local level, is key to implementing the relocation.
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One of the main challenges facing online and offline path planners is the uncertainty in the magnitude and direction of the environmental energy because it is dynamic, changeable with time, and hard to forecast. This thesis develops an artificial intelligence for a mobile robot to learn from historical or forecasted data of environmental energy available in the area of interest which will help for a persistence monitoring under uncertainty using the developed algorithm.