Autonomous vehicles depend on an accurate perception of their surroundings. For this purpose, different approaches are used to detect traffic participants such as cars, cyclists, and pedestrians, as well as static obj...
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ISBN:
(数字)9781737749721
ISBN:
(纸本)9781665489416
Autonomous vehicles depend on an accurate perception of their surroundings. For this purpose, different approaches are used to detect traffic participants such as cars, cyclists, and pedestrians, as well as static objects. A commonly used method is object detection and classification in camera images. However, due to the limited field of view of camera images, detecting in the entire environment of the ego-vehicle is an additional challenge. Some solutions include the use of catadioptric cameras or clustered surround view camera systems that require a large installation height. In multi-camera setups, an additional step is required to merge objects from overlapping areas between cameras. As an alternative to these systems, we present a real-time capable image stitching method to improve the horizontal field of view for object detection in autonomous driving. To do this, we use a spherical camera model and determine the overlapping area of the neighboring images based on the calibration. Furthermore, lidar measurements are used to improve image alignment. Finally, seam carving is applied to optimize the transition between the images. We tested our approach on a modular redundant sensor platform and on the publicly available nuScenes dataset. In addition to qualitative results, we evaluated the stitched images using an object detection network. Moreover, the real-time capability of our image stitching method is shown in a runtime analysis.
Numerous performance indicators exist for semiconductor manufacturing *** studies have been conducted regarding the performance optimization of semiconductor manufacturing ***,because of the complex manufacturing proc...
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Numerous performance indicators exist for semiconductor manufacturing *** studies have been conducted regarding the performance optimization of semiconductor manufacturing ***,because of the complex manufacturing processes,potential complementary or inhibitory correlations may exist among performance indicators,which are difficult to demonstrate *** analyze the correlation between the performance indicators,this study proposes a performance evaluation system based on the mathematical significance of each performance indicator to design statistical *** samples can be obtained by conducting simulation experiments through the performance evaluation *** Pearson correlation coefficient method and canonical correlation analysis are used on the received samples to analyze linear correlations between the performance *** the investigation,we found that linear and other complex correlations exist between the performance *** finding can contribute to our future studies regarding performance optimization for the scheduling problems of semiconductor manufacturing.
In various applications in the field of control engineering the estimation of the state variables of dynamic systems in the presence of unknown inputs plays an important role. Existing methods require the so-called ob...
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Trajectory planning is one of the key technologies in the manipulator motion system, and the effectiveness of the manipulator as a whole is directly influenced by this technology. Thus, accurate and effective trajecto...
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This vances tutorial in statistical survey provides learning an theory overview relevant of recent to control ad- and system identification featuring non-asymptotics. While there has been substantial progress across a...
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This study explores linear encryption techniques to protect against information-based stealthy attacks on re-mote state estimation. Utilizing smart sensors equipped with local Kalman filters, the system transmits inno...
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ISBN:
(数字)9798331518493
ISBN:
(纸本)9798331518509
This study explores linear encryption techniques to protect against information-based stealthy attacks on re-mote state estimation. Utilizing smart sensors equipped with local Kalman filters, the system transmits innovations rather than raw measurements via wireless networks. However, this transmission is susceptible to malicious data interception and manipulation by attackers. To safeguard against these stealthy threats, encryption and decryption modules are integrated into the system. This research aims to assess the effectiveness of the encryption strategy when faced with information-based stealthy attacks. A key contribution of this paper is the adoption of the most comprehensive attack models, moving away from the conventional reliance on innovation-based linear attack models. Our results demonstrate that the proposed linear encryption approach effectively mitigates stealthy attacks under certain mild conditions. The efficacy of the encryption is further validated through numerical examples, corroborating the theoretical advancements presented in this paper.
Multi-mode oscillation (MMO) is more prone to happen in the offshore wind farm (OWF) than the onshore, which seriously impacts the safe operation of the system. In this paper, the mechanism for the MMO of the OWF is a...
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A feedback control design is proposed for stochastic systems with finite second moment which aims at maximising the region of attraction of the equilibrium point. Polynomial Chaos (PC) expansions are employed to repre...
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A feedback control design is proposed for stochastic systems with finite second moment which aims at maximising the region of attraction of the equilibrium point. Polynomial Chaos (PC) expansions are employed to represent the stochastic closed loop system by a higher dimensional set of deterministic equations. By using the PC expanded system representation, the available information on the uncertainty affecting the system explicitly enters the control design problem. Further, this allows Lyapunov methods for deterministic systems to be used to formulate the stability criteria certifying the region of attraction. These criteria are parametrized by the feedback gain and formulated in a polynomial optimization program which is solved using sum-of-squares methods. This approach offers flexibility in the choice of the stochastic feedback law and accounts for input constraints. The application is demonstrated by two numerical examples.
Since the earliest conceptualizations by Lee and Markus, and Propoi in the 1960s, Model Predictive control (MPC) has become a major success story of systems and control with respect to industrial impact and with respe...
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