Reconstruction of intersecting surface models from scanned data for styling design

This paper presents a new method for reconstructing a surface model from scanned data as a \(\mathrm{C}^0\) composite surface. The surface is represented by intersecting underlying surfaces (U-surfaces), which are reconstructed from their respective parts segmented according to sweep-based modeling. However, even if each U-surface is successfully reconstructed, a surface model for the scanned data cannot be guaranteed to be desirably represented by a composite surface of those U-surfaces. Therefore, the proposed method reconstructs adjacent U-surfaces such that their intersecting curve represents part of feature lines, which are slightly offset from the scanned data, and has as small a torsion as possible. Compared with conventional approaches that naively fit a single patch to whole or some segmented parts, the method provides a guiding principle for the generation of surface models that are more suitable for styling design. The experimental results demonstrate that desirable models can be generated from real-world scanned data.

     

Inexpensive Reconstruction and Rendering of Realistic Roadside Landscapes

In this paper, we present an inexpensive approach to create highly detailed reconstructions of the landscape surrounding a road. Our method is based on a space‐efficient semi‐procedural representation of the terrain and vegetation supporting high‐quality real‐time rendering not only for aerial views but also at road level. We can integrate photographs along selected road stretches. We merge the point clouds extracted from these photographs with a low‐resolution digital terrain model through a novel algorithm which is robust against noise and missing data. We pre‐compute plausible locations for trees through an algorithm which takes into account perceptual cues. At runtime we render the reconstructed terrain along with plants generated procedurally according to pre‐computed parameters. Our rendering algorithm ensures visual consistency with aerial imagery and thus it can be integrated seamlessly with current virtual globes.     

Simultaneous Achievement of Open and Closed Loop Diagonal Dominance Through Constant Feedback

This paper proposes a new and low complexity technique for the simultaneous achievement of open and closed loop diagonal dominance for uncertain plants. The method is based on the introduction of a static high gain inner feedback which modifies the plant to attain a diagonal dominant open loop compensated plant. The sufficient, easy to use, conditions derived for the open loop diagonal dominance also assure the simultaneous achievement of closed loop diagonal dominance under soft assumptions on the diagonal elements of the decoupled controller robustly stabilizing the plant. These assumptions agree with the usual closed‐loop performance specifications, so that closed‐loop diagonal dominance is achieved without any extra complication on the controller design procedure. The main merits of the present method are: applicability to uncertain plants, ease of implementation and low computational cost. Three examples taken from the relevant literature, are given to show the effectiveness of the proposed approach.     

A patch-based approach to 3D plant shoot phenotyping

The emerging discipline of plant phenomics aims to measure key plant characteristics, or traits, though as yet the set of plant traits that should be measured by automated systems is not well defined. Methods capable of recovering generic representations of the 3D structure of plant shoots from images would provide a key technology underpinning quantification of a wide range of current and future physiological and morphological traits. We present a fully automatic approach to image-based 3D plant reconstruction which represents plants as series of small planar sections that together model the complex architecture of leaf surfaces. The initial boundary of each leaf patch is refined using a level set method, optimising the model based on image information, curvature constraints and the position of neighbouring surfaces. The reconstruction process makes few assumptions about the nature of the plant material being reconstructed. As such it is applicable to a wide variety of plant species and topologies, and can be extended to canopy-scale imaging. We demonstrate the effectiveness of our approach on real images of wheat and rice plants, an artificial plant with challenging architecture, as well as a novel virtual dataset that allows us to compute distance measures of reconstruction accuracy. We also illustrate the method’s potential to support the identification of individual leaves, and so the phenotyping of plant shoots, using a spectral clustering approach.     

Robust Repetitive Control and Disturbance Rejection Based on Two‐Dimensional Model and Equivalent‐Input‐Disturbance Approach

A new configuration of a modified repetitive‐control system has been devised for a class of strictly proper plants that suppresses exogenous disturbances and uncertainties in the dynamics of the plant. It extends the applicability of the control system. The system consists of four parts: a two‐dimensional augmented model of the plant, which takes into account the difference in characteristics between continuous control and discrete learning in repetitive control; an equivalent‐input‐disturbance estimator; a state observer; and a state‐feedback controller. A robust‐stability condition expressed in terms of a linear matrix equality is used to determine the gains of the observer and the controller. Finally, a comparison of our method with repetitive control based on linear active disturbance rejection control (LADRC) shows how effective our method is and that it is superior to LADRC‐based repetitive control.     

Protocol sequence and control co‐design for a collection of networked control systems

This paper is concerned with the simultaneous stabilization of a collection of plants shared by the wireless network with capacity limitation. We use most regular binary sequences (MRBS) to control the medium access status of the plants. The design procedure of the scheduling policy translates to determine two parameters of the MRBS. With the MRBS protocol, each plant is essentially a sampled‐data control system with time varying sampling intervals. We derive a sufficient condition for determining the MRBS protocol that guarantees the controllability, observability, and stability of each plant. Most importantly, we give a methodology for MRBS protocol and controller co‐design, in which the controller has switching gains that are piecewise constant and dependent on the sampling intervals yielded by the MRBS. The main results are established using piecewise Lyapunov functional and the average dwell time technique. It is shown that the method can guarantee simultaneous stabilization of the collection of plants robustly in situations where the controller gain does not match the sampling interval or the sampling interval violates the maximum allowable transmission interval criteria. A numerical example is given to demonstrate the effectiveness of the co‐design method. Copyright © 2015 John Wiley & Sons, Ltd.     

Gain-scheduled, model-based anti-windup for LPV systems

The aim of this paper is to show that a recently proposed technique for anti-windup control of exponentially unstable plants can be easily extended to solve the corresponding robust anti-windup problem for linear parameter varying systems, for which the time varying parameters are measured online. The proposed technique is minimally conservative with respect to the size of the resulting operating region (which coincides, up to an arbitrarily small quantity, with the largest set on which asymptotic stability can be guaranteed for the considered plant with the given saturation level and uncertainty characteristics), and is not limited to plants having only small uncertainties or being open-loop stable.     

基于叶片识别的侵入式室内植物建模

由于室内植物的叶片存在大量自遮挡,为了得到植物的完整三维信息,往往需要用户手动裁剪、扫描和配准叶片.针对该问题,提出了利用实例分割网络进行叶片识别并选取被裁剪叶片的方法.通过总结植物叶片形状与分布特征,建立虚拟植物模型,渲染大量带叶片轮廓信息的图片来训练实例分割网络,避免了耗费大量精力标注真实植物叶片.进一步提出了自动化建模系统,根据单个视角下观察到的植物图像自动选择被裁剪的叶片,并获得该叶片的三维模型;调整相机位置让更多的叶片被检测到并剪掉,以恢复植物的三维信息.使用该系统对绿萝叶片、鸭脚木和花烛3种虚拟植物进行了测试,并评估重建的整株植物重合度、叶片重合度和叶片占比,结果显示使用本文方法重建的植物模型能更完整地恢复原始植物的三维信息.     

Realization of simple adaptive control by using parallel feedforward compensator

A problem is dealt with concerning a practical design scheme for a multi-input/multi-output simple adaptive control (SAC) system. The SAC method which was first derived as a sort of the direct model following adaptive control based on the command generator tracker (CGT) technique was fundamentally applicable to plants satisfying the so-called almost strictly positive real (ASPR) condition. However, the method can be applied to non-ASPR plants by using a parallel feedforward compensator (PFC), which makes the augmented plant including PFC be ASPR. Such a technique was proposed by Bar-Kana for plants satisfying the output feedback stabilizable condition. As an extension, the authors have proposed a simple and concrete PFC design procedure for SISO non-ASPR plants. The special feature of this proposal is that the method can be applicable to non-ASPR plants as the minimum phase system. The main aim of the paper is to give a practical design procedure of PFC for MIMO plants as a natural extension of the SISO case, so that an actual realization of MIMO SAC can be attained for a broad class of MIMO plants. The effectiveness of the proposed method is also confirmed through numerical simulations.     

Viewing‐angle characterization of reflective‐type liquid‐crystal displays by using an ellipsoidal mirror and a two‐dimensional CCD camera

A new photometry to perform the viewing‐angle characterization for reflective‐type LCDs has been developed. The optics consists of a rotating ellipsoidal mirror and a 2‐D CCD camera. The information obtained by this photometry includes the viewing‐angle characteristics of reflectance, contrast ratio, and chromaticity coordinates, which are comparable to gonioscopic photometry in terms of accuracy. Both the illuminating polar angle and azimuth angle can be scanned. The measurement time for this method is as short as that for conoscopic photometry when using a 2‐D CCD camera. An instrument equipped with light‐polarizing devices is already available. If analytic software was available, viewing‐angle characterization could be determined by a polarization analysis.     

Robust plant by plant control design using model‐error tracking sets

This paper presents a method for designing a robust two‐degree‐of‐freedom control scheme, capable of satisfying multiple model‐error specifications on a plant by plant basis. Traditional quantitative feedback theory methods generally use a single model‐error or above‐below magnitude tracking specification, which can result in overdesign for plants located away from the bounding conditions. The performance specifications are also generally hand‐tuned, or iteratively adjusted to keep the underlying time‐domain signals within permissible levels. Our method aims to perform a model‐error design on a per‐plant basis, such that each plant's corresponding model tracking has equal weighting given the plant's inherent feedback requirements and capability. The quantitative feedback theory method allows this per‐plant approach to be undertaken with ease. Additionally, sufficiently low‐order model specifications are designed using simple optimisation, which take into account performance limiting effects, such as non‐minimum phase behaviour and signal constraints. A worked example is presented, showing the viability and transparency of the proposed method.     

Estimation of plant species by classifying plants and leaves in combination

Information on which weed species are present within agricultural fields is a prerequisite when using robots for site‐specific weed management. This study proposes a method of improving robustness in shape‐based classifying of seedlings toward natural shape variations within each plant species. To do so, leaves are separated from plants and classified individually together with the classification of the whole plant. The classification is based on common, rotation‐invariant features. Based on previous classifications of leaves and plants, confidence in correct assignment is created for the plants and leaves, and this confidence is used to determine the species of the plant. By using this approach, the classification accuracy of eight plants species at early growth stages is increased from 93.9% to 96.3%.     

Non‐parametric linear time‐invariant extensions of non‐invertible and backlash plant

A rigorous validation for the use of a set of linear time‐invariant models as a surrogate in the design of controllers for uncertain nonlinear systems, which are invertible as one‐to‐one operators, such as used in the nonlinear quantitative feedback theory (NLQFT) design methodology has been given by Baños and Bailey. This paper presents a similar validation but weakens the requirement on the invertibility of the nonlinear plant by application of Kakutani's fixed‐point theorem and an incremental gain constraint on the plant within its operational envelope. The set of linear time‐invariant models to be used for design is shown to be an extension (termed here the linear time‐invariant extension—LTIE) of the nonlinear plant restricted to the desired output operating space. A new non‐parametric approach to the modelling of the LTIE is proposed which is based on Fourier transforms of the plant I/O data and which accordingly may be based solely on experimental testing without the need for an explicit parametric plant model. This new approach thus extends the application of robust linear controller design methods (including those of NLQFT) to nonlinear plants with set‐valued (multi‐valued) inverses such as those containing backlash and also to plants for which explicit parametric models are difficult to obtain. The method is illustrated by application of the non‐parametric approach to an NLQFT tracking controller design for a mechanical backlashed servomechanism problem. Copyright © 2013 John Wiley & Sons, Ltd.     

Interactive Modeling and Authoring of Climbing Plants

We present a novel system for the interactive modeling of developmental climbing plants with an emphasis on efficient control and plausible physics response. A plant is represented by a set of connected anisotropic particles that respond to the surrounding environment and to their inner state. Each particle stores biological and physical attributes that drive growth and plant adaptation to the environment such as light sensitivity, wind interaction, and physical obstacles. This representation allows for the efficient modeling of external effects that can be induced at any time without prior analysis of the plant structure. In our framework we exploit this representation to provide powerful editing capabilities that allow to edit a plant with respect to its structure and its environment while maintaining a biologically plausible appearance. Moreover, we couple plants with Lagrangian fluid dynamics and model advanced effects, such as the breaking and bending of branches. The user can thus interactively drag and prune branches or seed new plants in dynamically changing environments. Our system runs in real‐time and supports up to 20 plant instances with 25k branches in parallel. The effectiveness of our approach is demonstrated through a number of interactive experiments, including modeling and animation of different species of climbing plants on complex support structures.     

A Measurement‐Based Approach for Designing Fixed‐Order Controllers for Unknown Closed‐Loop Architecture

This paper presents a new technique to design fixed‐structure controllers for linear unknown systems using a set of measurements. In model‐based approaches, the measured data are used to identify a model of the plant for which a suitable controller can be designed. Due to the fact that real processes cannot be described perfectly by mathematical models, designing controllers using such models to guarantee some desired closed‐loop performance is a challenging task. Hence, a possible alternative to model‐based methods is to directly utilize the measured data in the design process. We propose an approach to designing structured controllers using a set of closed‐loop frequency‐domain data. The principle of such an approach is based on computing the parameters of a fixed‐order controller for which the closed‐loop frequency response fits a desired frequency response that describes some desired performance indices. This problem is formulated as an error minimization problem, which can be solved to find suitable values of the controller parameters. The main feature of the proposed control methodology is that it can be applied to stable and unstable plants. Additionally, the design process depends on a pre‐selected controller structure, which allows for the selection of low‐order controllers. An application of the proposed method to a DC servomotor system is presented to experimentally validate and demonstrate its efficacy.     

Control of linear plants with zeros and slowly varying parameters

A reduction of order technique is developed which is useful in controller design for single-input, single-output, linear plants which have transfer functions with zeros and parameters which vary slowly compared to the response time of the plant. The controller design is based on a Liapunov-like method and employs a model reference. The reduction of order technique allows the control signal to be generated from the plant output and only its firstn-m-1derivatives if the plant transfer function has annth order denominator and anmth order numerator and if the transfer function hasmknown fixed poles.     

交互式结构光视觉系统

提出一种交互式结构光三维重建系统,在传统的结构光视觉的基础上,增加交互能力.通过人机交互的形式,对三维重建后的物体进行评价,对置信度较低的重建结果,返回原始的二维图像,利用人的知识对获取的结构光图像进行人工干预,然后再进行重建.对于部分物体还利用神经网络对系统进行自学习.实践结果表明,能够扩展结构光视觉系统的应用范围,对于因反射原因而用传统结构光方法难以获取的物体,也可以获得较好的结果.     

3D Motion Completion in Crowded Scenes

Crowded motions refer to multiple objects moving around and interacting such as crowds, pedestrians and etc. We capture crowded scenes using a depth scanner at video frame rates. Thus, our input is a set of depth frames which sample the scene over time. Processing such data is challenging as it is highly unorganized, with large spatio‐temporal holes due to many occlusions. As no correspondence is given, locally tracking 3D points across frames is hard due to noise and missing regions. Furthermore global segmentation and motion completion in presence of large occlusions is ambiguous and hard to predict. Our algorithm utilizes Gestalt principles of common fate and good continuity to compute motion tracking and completion respectively. Our technique does not assume any pre‐given markers or motion template priors. Our key‐idea is to reduce the motion completion problem to a 1D curve fitting and matching problem which can be solved efficiently using a global optimization scheme. We demonstrate our segmentation and completion method on a variety of synthetic and real world crowded scanned scenes.     

Flower reconstruction from a single photo

We present a semi‐automatic method for reconstructing flower models from a single photograph. Such reconstruction is challenging since the 3D structure of a flower can appear ambiguous in projection. However, the flower head typically consists of petals embedded in 3D space that share similar shapes and form certain level of regular structure. Our technique employs these assumptions by first fitting a cone and subsequently a surface of revolution to the flower structure and then computing individual petal shapes from their projection in the photo. Flowers with multiple layers of petals are handled through processing different layers separately. Occlusions are dealt with both within and between petal layers. We show that our method allows users to quickly generate a variety of realistic 3D flowers from photographs and to animate an image using the underlying models reconstructed from our method.