3 resultados para Walls

em QSpace: Queen's University - Canada


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In geotechnical engineering, the stability of rock excavations and walls is estimated by using tools that include a map of the orientations of exposed rock faces. However, measuring these orientations by using conventional methods can be time consuming, sometimes dangerous, and is limited to regions of the exposed rock that are reachable by a human. This thesis introduces a 2D, simulated, quadcopter-based rock wall mapping algorithm for GPS denied environments such as underground mines or near high walls on surface. The proposed algorithm employs techniques from the field of robotics known as simultaneous localization and mapping (SLAM) and is a step towards 3D rock wall mapping. Not only are quadcopters agile, but they can hover. This is very useful for confined spaces such as underground or near rock walls. The quadcopter requires sensors to enable self localization and mapping in dark, confined and GPS denied environments. However, these sensors are limited by the quadcopter payload and power restrictions. Because of these restrictions, a light weight 2D laser scanner is proposed. As a first step towards a 3D mapping algorithm, this thesis proposes a simplified scenario in which a simulated 1D laser range finder and 2D IMU are mounted on a quadcopter that is moving on a plane. Because the 1D laser does not provide enough information to map the 2D world from a single measurement, many measurements are combined over the trajectory of the quadcopter. Least Squares Optimization (LSO) is used to optimize the estimated trajectory and rock face for all data collected over the length of a light. Simulation results show that the mapping algorithm developed is a good first step. It shows that by combining measurements over a trajectory, the scanned rock face can be estimated using a lower-dimensional range sensor. A swathing manoeuvre is introduced as a way to promote loop closures within a short time period, thus reducing accumulated error. Some suggestions on how to improve the algorithm are also provided.

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My dissertation examines the traces of inverse (mytho)mysticism, more synchronous with mythical alchemy than transcendent mystery, in H.D.’s mature work (1946-1961). Whereas H.D.’s earliest works respond to a fin de siècle occultism and a collective psyche troubled by the eschatological distress that, as Susan Acheson writes, “was widespread amongst modernist writers grappling with …world events and with the implications of Nietzsche’s inaugural annunciation of modernity in terms of the death of God” (187), her later oeuvre is dedicated to the same work of soul undertaken by the “secret cult of Night” in Vale Ave. Here, her thematic scope faces two ways: backward to ancient Greek mystery cults and their palingenesic rites and forward to depth psychologists searching for the Soul of the World. Vale Ave plays a pronounced role in my study as symbolic guide; in its seventy-four sequences the layering of time in the “trilogy” of past, present, and future that H.D. had explored during the years of the Second World War in order to get behind the fallen walls of cause and effect collapses into two distinct phases of human origin—“meeting” (evolution) and “parting” (involution)—and the poem invites Lilith and Lucifer to be its archetypal guides. My method for the study is imaginal, entering such disciplines as history, philosophy, and theology and bringing psychological understanding to them. John Walsh’s introduction to Vale Ave notes H.D.’s theme “that the human psyche exists in a dimension outside of time and space as well as within them. In Vale Ave, H.D. presents the extremity of this dual-dimensionality: metempsychosis” (vii). However, the concept that H.D. investigates is more than a literary processus of characters who adopt different masks and appear at various junctures in a chronological unwinding of history. I explore H.D.'s works as part of a Modernist tradition of writing “books of the dead” designed not to guide the soul after death, but to draw the gaze upon “a nearer thing,” as H.D. writes in Erige Cor Tuum Ad Me In Caelum, the wisdom intrinsic in the spirit of life itself.

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Without an absolute position sensor (e.g., GPS), an accurate heading estimate is necessary for proper localization of an autonomous unmanned vehicle or robot. This paper introduces direction maps (DMs), which represent the directions of only dominant surfaces of the vehicle’s environment and can be created with negligible effort. Given an environment with reoccurring surface directions (e.g., walls, buildings, parked cars), lines extracted from laser scans can be matched with a DM to provide an extremely lightweight heading estimate that is shown, through experimentation, to drastically reduce the growth of heading errors. The algorithm was tested using a Husky A200 mobile robot in a warehouse environment over traverses hundreds of metres in length. When a simple a priori DM was provided, the resulting heading estimation showed virtually no error growth.