A smooth time-varying controller is proposed to simultaneously address the stabilization and tracking problems of nonholonomic mobile robots for most admissible reference trajectories without switching. The controller is developed with the aid of a delicately designed time-varying signal and Lyapunov method. Computational simplification and asymptotic convergence of regulation or tracking errors are achieved by the proposed controller. Our approach provides an interesting way to unify the existing results on point stabilization and trajectory tracking of mobile robots. The simulation and experimental results on a wheeled mobile robot are presented to demonstrate the effectiveness of the proposed controller.Index Terms-Lyapunov method, mobile robots, nonholonomic systems, stabilization and tracking, time-varying feedback. 1063-6536
Existing enhancement methods are empirically expected to help the high-level end computer vision task: however, that is observed to not always be the case in practice. We focus on object or face detection in poor visibility enhancements caused by bad weathers (haze, rain) and low light conditions. To provide a more thorough examination and fair comparison, we introduce three benchmark sets collected in real-world hazy, rainy, and lowlight conditions, respectively, with annotated objects/faces. We launched the UG 2+ challenge Track 2 competition in IEEE CVPR 2019, aiming to evoke a comprehensive discussion and exploration about whether and how low-level vision techniques can benefit the high-level automatic visual recognition in various scenarios. To our best knowledge, this is the first and currently largest effort of its kind. Baseline results by cascading existing enhancement and detection models are reported, indicating the highly challenging nature of our new data as well as the large room for further technical innovations. Thanks to a large participation from the research community, we are able to analyze representative team solutions, striving to better identify the strengths and limitations of existing mindsets as well as the future directions.Index Terms-Poor visibility environment, object detection, face detection, haze, rain, low-light conditions *The first two authors Wenhan Yang and Ye Yuan contributed equally. Ye Yuan and Wenhan Yang helped prepare the dataset proposed for the UG2+ Challenges, and were the main responsible members for UG2+ Challenge 2019 (Track 2) platform setup and technical support. Wenqi Ren, Jiaying Liu, Walter J. Scheirer, and Zhangyang Wang were the main organizers of the challenge and helped prepare the dataset, raise sponsors, set up evaluation environment, and improve the technical submission. Other authors are the group members of winner teams in UG2+ challenge Track 2 contributing to the winning methods.
ITO thin films were deposited on glass substrates by d.c. magnetron sputtering with varied oxygen flow rates. It was found that the optical absorption decreases and optical absorption edge has blue shifts with the increasing oxygen flow rate. Oxygen vacancy concentration was characterized and analyzed by XPS. It is shown that the oxygen vacancy concentration increases with oxygen flow rates, which is a different observation from the current understanding. The energy band structures associated with different vacancy concentrations of ITO were calculated using the first-principle based on density functional theory. The calculation results show that the increase of oxygen vacancies induces the increase of bands below Fermi level as well as the presence of a second band gap, which accounts for effects of the oxygen vacancies on the blue shifts.
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