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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A study on cheap robust sensing for obstacle avoidance guidance based on bio-sonar strategy of bats / コウモリのソナー戦略を模倣した障害物回避行動のためのチープロバストなセンシングに関する研究 / コウモリ ノ ソナー センリャク オ モホウ シタ ショウガイブツ カイヒ コウドウ ノ タメ ノ チープ ロバストナ センシング ニカンスル ケンキュウ

山田 恭史, Yasufumi Yamada 22 March 2017 (has links)
コウモリは1送信2受信器のミニマルな超音波センシングデザインからは想像できない,高度な3次元飛行を実現させている.本論文では,①繰り返し同じ障害物環境下を飛行するコウモリの未知と既知の空間に対する音響センシング行動の違いを比較した.さらに,②未知環境飛行時に見られる特徴的な空間スキャニングの行動パターンをモデル化し,自律走行車を用いてコウモリの行動の有用性を実環境センシングのふるまいから定量的に評価した. / Bats possess a highly developed biosonar system that can be regarded as the minimum sensor requirement for three-dimensional spatial sensing. The present study 1) experimentally investigated changes in the pulse direction, pulse emission timing and flight path of CF-FM bats during an obstacle avoidance flight as the bats became familiar with the space around them and 2) expressed behavioral principles observed in the bats during flight, especially in an unfamiliar space, using an algorithm and then embedded the principles into an autonomous vehicle equipped with simple ultrasound sensors. The findings of this world-leading biomimetic research offer new possibilities for artificial-intelligence navigation systems. / 博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University
2

Developing an autosteering of road motor vehicles in slippery road conditions / 滑りやすい路面条件における自動車の自動操縦に関する研究 / スベリヤスイ ロメン ジョウケン ニオケル ジドウシャ ノ ジドウ ソウジュウ ニカンスル ケンキュウ

Natalia Mihajlovna Alekseeva, Natalia Alekseeva 19 September 2020 (has links)
In the nearest future, the human driver is viewed as a reliable backup even for the fully automated road motor vehicles (cars). Indeed, the driver is assumed to swiftly take the control of the car in cases of suddenly occurring (i) challenging environmental conditions, (ii) complex unforeseen driving situations, or (iii) degradation of performance of the car. However, due to the cognitive overload in such a sudden, stressful takeover of the control, the driver would often experience the startle effect, which usually results in an unconscious, instinctive, yet incorrect response. An extreme case of startle is freezing, in which the driver might be incapable to respond to the sudden takeover of control at all. The possible approaches to alleviate the startle during the takeover of control (i.e., the automation startle) include an offset- (i.e., either early- or delayed-), gradual yielding the controls to the driver. In the cases considered above, however, these approaches are hardly applicable because of (i) the presumed unpredictability of the events that result in the need of takeover of control, and (ii) the severe time constraints of the latter. Conversely, the objective of our research is to propose an approach of minimizing the need of yielding the control to the driver in challenging environmental conditions by guaranteeing an adequate automated control in these conditions. Focusing on slippery roads as an instance of challenging conditions, and steering control as an instance of control, we aim at developing such an automated steering that controls the car adequately in various road surfaces featuring low friction coefficients without the need of driver’s intervention.In order to develop such an automated steering we employed an in-house evolutionary computation framework – XML-based genetic programming (XGP) – which offers a flexible, portable, and human readable representation of the evolved optimal steering functions. The trial runs of the evolved steering functions were performed in the Open Source Racing Car Simulator (TORCS), which features a realistic, yet computationally efficient simulation of the car and its environment. The obtained experimental results indicate that due to the challenging dynamics of the unstable car on slippery roads, neither the canonical (tuned) servo-control (as a variant of PD) nor the (tuned) PID-controller could control the car adequately on slippery roads. On the other hand, the controller, featuring a relaxed, arbitrary structure evolved by XGP outperforms both the servo- and PID controllers in that it results in a minimal deviation of the car from its intended trajectory in rainy, snowy, and icy road conditions. Moreover, the evolved steering that employs anticipated perceptions is even superior as it could anticipate the imminent understeering of the car at the entry of the turns and consequently – to compensate for such an understeering by proactively turning the steering wheels in advance – well before entering the turn. The obtained results suggest a human competitiveness of the evolved automated steering as it outperforms the commonly used alternative steering controllers proposed by human experts. The research could be viewed as a step towards the evolutionary development of automated steering of cars in challenging environmental conditions. / 博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University

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