Controller reduction for effective interdisciplinary design of active structures

Control problems of large aerospace structures are intrinsically interdisciplinary and require strategies which address the complete interaction between flexible structures, electromechanical actuators and sensors, and feedback control algorithms. Current research and future directions which will require an interdisciplinary team effort in dynamics, control and optimization of such structures are being surveyed. It is generally agreed that the dynamics of space structures require large scale discrete modeling, resulting in thousands of discrete unknowns. Proven control strategies, on the other hand, employ a low order controller that is based on a reduced order model of structures. Integration of such low order controllers and large scale dynamics models often leads to serious deterioration of the closed loop stability margin and even instability. To alleviate this stability deterioration while low order controllers remain effective, the following approach was investigated: (1) retain low order controllers based on reduced order models of structures as the basic control strategy; (2) introduce a compensator that will directly account for the deterioration of stability margin due to controller-structure integration; and (3) assess overall performance of the integrated control structure system by developing measures of suboptimality in the combination of (1) and (2). The benefits include: simplicity in the design of basic controllers, thus facilitating the optimization of structure control interactions; increased understanding of the roles of the compensator so as to modify the structure as well as the basic controller, if necessary, for improved performance; and adaptability to localize controllers by viewing the compensator as a systems integration filter

The use of linked lists in the simulation of controller-structure interaction

An algorithm for the computer simulation of large space structures under active control is considered. Linked lists are used in a matrix data structure to implement the trapezoidal rule on the system differential equations. The use of the trapezoidal rule ensures that the numerical stability is equivalent to the system stability, which is essential for this type of simulation. The sparsity of the system matrices is exploited by the linked lists, and the algorithm efficiently steps through the lists in an orderly fashion. Results of simulations on a NASA large space structure experiment are reported

Parametric editing of clothed 3D avatars

Easy editing of a clothed 3D human avatar is central to many practical applications. However, it is easy to produce implausible, unnatural looking results, since subtle reshaping or pose alteration of avatars requires global consistency and agreement with human anatomy. Here, we present a parametric editing system for a clothed human body, based on use of a revised SCAPE model. We show that the parameters of the model can be estimated directly from a clothed avatar, and that it can be used as a basis for realistic, real-time editing of the clothed avatar mesh via a novel 3D body-aware warping scheme. The avatar can be easily controlled by a few semantically meaningful parameters, 12 biometric attributes controlling body shape, and 17 bones controlling pose. Our experiments demonstrate that our system can interactively produce visually pleasing results

Realtime reconstruction of an animating human body from a single depth camera

We present a method for realtime reconstruction of an animating human body, which produces a sequence of deforming meshes representing a given performance captured by a single commodity depth camera. We achieve realtime single-view mesh completion by enhancing the parameterized SCAPE model. Our method, which we call Realtime SCAPE, performs full-body reconstruction without the use of markers. In Realtime SCAPE, estimations of body shape parameters and pose parameters, needed for reconstruction, are decoupled. Intrinsic body shape is first precomputed for a given subject, by determining shape parameters with the aid of a body shape database. Subsequently, per-frame pose parameter estimation is performed by means of linear blending skinning (LBS); the problem is decomposed into separately finding skinning weights and transformations. The skinning weights are also determined offline from the body shape database, reducing online reconstruction to simply finding the transformations in LBS. Doing so is formulated as a linear variational problem; carefully designed constraints are used to impose temporal coherence and alleviate artifacts. Experiments demonstrate that our method can produce full-body mesh sequences with high fidelity

Fast capture of textured full-body avatar with RGB-D cameras

We present a practical system which can provide a textured full-body avatar within three seconds. It uses sixteen RGB-depth (RGB-D) cameras, ten of which are arranged to capture the body, while six target the important head region. The configuration of the multiple cameras is formulated as a constraint-based minimum set space-covering problem, which is approximately solved by a heuristic algorithm. The camera layout determined can cover the fullbody surface of an adult, with geometric errors of less than 5 mm. After arranging the cameras, they are calibrated using a mannequin before scanning real humans. The 16 RGB-D images are all captured within 1 s, which both avoids the need for the subject to attempt to remain still for an uncomfortable period, and helps to keep pose changes between different cameras small. All scans are combined and processed to reconstruct the photo-realistic textured mesh in 2 s. During both system calibration and working capture of a real subject, the high-quality RGB information is exploited to assist geometric reconstruction and texture stitching optimization

Synergistic toughening and electrical functionalization of an epoxy using MWCNTs and silane- /plasma-activated basalt fibers

This work studied the effects of adding short basalt fibers (BFs) and multi-walled carbon nanotubes (MWCNTs), both separately and in combination, on the mechanical properties, fracture toughness, and electrical conductivity of an epoxy polymer. The surfaces of the short BFs were either treated using a silane coupling agent or further functionalized by atmospheric plasma to enhance the adhesion between the BFs and the epoxy. The results of a single fiber fragmentation test demonstrated a significantly improved BF/epoxy adhesion upon applying the plasma treatment to the BFs. This resulted in better mechanical properties and fracture toughness of the composites containing the plasma-activated BFs. The improved BF/epoxy adhesion also affected the hybrid toughening performance of the BFs and MWCNTs. In particular, synergistic toughening effects were observed when the plasma-activated BFs/MWCNTs hybrid modifiers were used, while only additive toughening effects occurred for the silane-sized BFs/MWCNTs hybrid modifiers. This work demonstrated a potential to develop strong, tough, and electrically conductive epoxy composites by adding hybrid BF/MWCNT modifiers.</p

Multiple-cue-based visual object contour tracking with incremental learning

This paper proposes a visual object contour tracking algorithm using a multi-cue fusion particle filter. A novel contour evolution energy is proposed which integrates an incrementally learnt model of object appearance with a parametric snake model. This energy function is combined with a mixed cascade particle filter tracking algorithm which fuses multiple observation models for object contour tracking. Bending energy due to contour evolution is modelled using a thin plate spline (TPS). Multiple order graph matching is performed between contours in consecutive frames. Both of the above are taken as observation models for contour deformation; these models are fused efficiently using a mixed cascade sampling process. The dynamic model used in our tracking method is further improved by the use of optical flow. Experiments on real videos show that our approach provides high performance object contour tracking

SuperMatching: feature matching using supersymmetric geometric constraints

Feature matching is a challenging problem at the heart of numerous computer graphics and computer vision applications. We present the SuperMatching algorithm for finding correspondences between two sets of features. It does so by considering triples or higher order tuples of points, going beyond the pointwise and pairwise approaches typically used. SuperMatching is formulated using a supersymmetric tensor representing an affinity metric that takes into account feature similarity and geometric constraints between features: Feature matching is cast as a higher order graph matching problem. SuperMatching takes advantage of supersymmetry to devise an efficient sampling strategy to estimate the affinity tensor, as well as to store the estimated tensor compactly. Matching is performed by an efficient higher order power iteration approach that takes advantage of this compact representation. Experiments on both synthetic and real data show that SuperMatching provides more accurate feature matching than other state-of-the-art approaches for a wide range of 2D and 3D features, with competitive computational cost