998 resultados para Reactive planning


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Planning in design processes is modeled in terms of connectivities between product developments. Each product development comprises a network of processes. Similarity between processes is analysed by a layered classification ranging from common components to shared design knowledge. The connectivities between products arising from similarities among products are represented by a multidimensional network. Design planning is described by flows or 'traffic' on this network which represents a structural model of complexity. Comparison is made with information based measures of the complexity of designs and processes.

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Managing protected areas implies dealing with complex social-ecological systems where multiple dimensions (social, institutional, economic and ecological) interact over time for the delivery of ecosystem services. Uni-dimensional and top-down management approaches have been unable to capture this complexity. Instead, new integrated approaches that acknowledge the diversity of social actors in the decision making process are required. In this paper we put forward a novel participatory assessment approach which integrates multiple methodologies to reflect different value articulating institutions in the case of a Natura 2000 network site in the Basque Country. It integrates within a social multi-criteria evaluation framework, both the economic values of ecosystem services through a choice experiment model and ecological values by means of a spatial bio-geographic assessment. By capturing confronting social and institutional conflicts in protected areas the participatory integrated assessment approach presented here can help decision makers for better planning and managing Natura 2000 sites.

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An examination is made of the current situation regarding fisheries planning in Nigeria, identifying areas where information is required to correct existing imbalances. The artisanal fishery, industrial/commercial fishery and aquaculture sectors and requirements for a comprehensive development policy in each sector are detailed

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Sensory-motor circuits course through the parietal cortex of the human and monkey brain. How parietal cortex manipulates these signals has been an important question in behavioral neuroscience. This thesis presents experiments that explore the contributions of monkey parietal cortex to sensory-motor processing, with an emphasis on the area's contributions to reaching. First, it is shown that parietal cortex is organized into subregions devoted to specific movements. Area LIP encodes plans to make saccadic eye movements. A nearby area, the parietal reach region (PRR), plans reaches. A series of experiments are then described which explore the contributions of PRR to reach planning. Reach plans are represented in an eye-centered reference frame in PRR. This representation is shown to be stable across eye movements. When a sequence of reaches is planned, only the impending movement is represented in PRR, showing that the area is more related to movement planning than to storing the memory of reach targets. PRR resembles area LIP in each of these properties: the two areas may provide a substrate for hand-eye coordination. These findings yield new perspectives on the functions of the parietal cortex and on the organization of sensory-motor processing in primate brains.

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Port authorities from around the world were surveyed to ascertain how administrators feel climate change might impact their operations, what level of change would be problematic, and how they plan to adapt to new conditions. The survey was distributed to 350 major ports through two leading international port organizations, the International Association of Ports and Harbors and the American Association of Port Authorities. (PDF contains 4 pages)

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The University of Hawaii Sea Grant College Program (UHSG) in partnership with the Hawaii Department of Land and Natural Resources (DLNR), Office of Conservation and Coastal Lands (OCCL) is developing a beach and dune management plan for Kailua Beach on the eastern shoreline of Oahu. The objective of the plan is to develop a comprehensive beach management and land use development plan for Kailua Beach that reflects the state of scientific understanding of beach processes in Kailua Bay and abutting shoreline areas and is intended to provide long-term recommendations to adapting to climate change including potential coastal hazards such as sea level rise. The development of the plan has lead to wider recognition of the significance of projected sea level rise to the region and provides the rational behind some of the land use conservation strategies. The plan takes on a critical light given global predictions for continued, possibly accelerated, sea-level rise and the ongoing focus of intense development along the Hawaiian shoreline. Hawaii’s coastal resource managers are faced with the daunting prospect of managing the effects of erosion while simultaneously monitoring and regulating high-risk coastal development that often impacts the shoreline. The beach and dune preservation plan is the first step in a more comprehensive effort prepare for and adapt to sea level rise and ensure the preservation of the beach and dune ecosystem for the benefit of present and future generations. The Kailua Beach and Dune Management plan is intended to be the first in a series of regional plans in Hawaii to address climate change adaptation through land use planning. (PDF contains 3 pages)

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According to the Millennium Ecosystem Assessment’s chapter “Coastal Systems” (Agardy and Alder 2005), 40% of the world population falls within 100 km of the coast. Agardy and Alder report that population densities in coastal regions are three times those of inland regions and demographic forecasts suggest a continued rise in coastal populations. These high population levels can be partially traced to the abundance of ecosystem services provided in the coastal zone. While populations benefit from an abundance of services, population pressure also degrades existing services and leads to increased susceptibility of property and human life to natural hazards. In the face of these challenges, environmental administrators on the coast must pursue agendas which reflect the difficult balance between private and public interests. These decisions include maintaining economic prosperity and personal freedoms, protecting or enhancing the existing flow of ecosystem services to society, and mitigating potential losses from natural hazards. (PDF contains 5 pages)

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This thesis explores the problem of mobile robot navigation in dense human crowds. We begin by considering a fundamental impediment to classical motion planning algorithms called the freezing robot problem: once the environment surpasses a certain level of complexity, the planner decides that all forward paths are unsafe, and the robot freezes in place (or performs unnecessary maneuvers) to avoid collisions. Since a feasible path typically exists, this behavior is suboptimal. Existing approaches have focused on reducing predictive uncertainty by employing higher fidelity individual dynamics models or heuristically limiting the individual predictive covariance to prevent overcautious navigation. We demonstrate that both the individual prediction and the individual predictive uncertainty have little to do with this undesirable navigation behavior. Additionally, we provide evidence that dynamic agents are able to navigate in dense crowds by engaging in joint collision avoidance, cooperatively making room to create feasible trajectories. We accordingly develop interacting Gaussian processes, a prediction density that captures cooperative collision avoidance, and a "multiple goal" extension that models the goal driven nature of human decision making. Navigation naturally emerges as a statistic of this distribution.

Most importantly, we empirically validate our models in the Chandler dining hall at Caltech during peak hours, and in the process, carry out the first extensive quantitative study of robot navigation in dense human crowds (collecting data on 488 runs). The multiple goal interacting Gaussian processes algorithm performs comparably with human teleoperators in crowd densities nearing 1 person/m2, while a state of the art noncooperative planner exhibits unsafe behavior more than 3 times as often as the multiple goal extension, and twice as often as the basic interacting Gaussian process approach. Furthermore, a reactive planner based on the widely used dynamic window approach proves insufficient for crowd densities above 0.55 people/m2. We also show that our noncooperative planner or our reactive planner capture the salient characteristics of nearly any dynamic navigation algorithm. For inclusive validation purposes, we show that either our non-interacting planner or our reactive planner captures the salient characteristics of nearly any existing dynamic navigation algorithm. Based on these experimental results and theoretical observations, we conclude that a cooperation model is critical for safe and efficient robot navigation in dense human crowds.

Finally, we produce a large database of ground truth pedestrian crowd data. We make this ground truth database publicly available for further scientific study of crowd prediction models, learning from demonstration algorithms, and human robot interaction models in general.