Local, hierarchic, and iterative reconstructors for adaptive optics

Adaptive optics systems for future large optical telescopes may require thousands of sensors and actuators. Optimal reconstruction of phase errors using relative measurements requires feedback from every sensor to each actuator, resulting in computational scaling for n actuators of n^2 . The optimum local reconstructor is investigated, wherein each actuator command depends only on sensor information in a neighboring region. The resulting performance degradation on global modes is quantified analytically, and two approaches are considered for recovering "global" performance. Combining local and global estimators in a two-layer hierarchic architecture yields computations scaling with n^4/3 ; extending this approach to multiple layers yields linear scaling. An alternative approach that maintains a local structure is to allow actuator commands to depend on both local sensors and prior local estimates. This iterative approach is equivalent to a temporal low-pass filter on global information and gives a scaling of n^3/2 . The algorithms are simulated by using data from the Palomar Observatory adaptive optics system. The analysis is general enough to also be applicable to active optics or other systems with many sensors and actuators

Towards retrieving force feedback in robotic-assisted surgery: a supervised neuro-recurrent-vision approach

Robotic-assisted minimally invasive surgeries have gained a lot of popularity over conventional procedures as they offer many benefits to both surgeons and patients. Nonetheless, they still suffer from some limitations that affect their outcome. One of them is the lack of force feedback which restricts the surgeon's sense of touch and might reduce precision during a procedure. To overcome this limitation, we propose a novel force estimation approach that combines a vision based solution with supervised learning to estimate the applied force and provide the surgeon with a suitable representation of it. The proposed solution starts with extracting the geometry of motion of the heart's surface by minimizing an energy functional to recover its 3D deformable structure. A deep network, based on a LSTM-RNN architecture, is then used to learn the relationship between the extracted visual-geometric information and the applied force, and to find accurate mapping between the two. Our proposed force estimation solution avoids the drawbacks usually associated with force sensing devices, such as biocompatibility and integration issues. We evaluate our approach on phantom and realistic tissues in which we report an average root-mean square error of 0.02 N.Peer ReviewedPostprint (author's final draft

Wind and boundary layers in Rayleigh-Benard convection. I: analysis and modeling

The aim of this paper is to contribute to the understanding and to model the processes controlling the amplitude of the wind of Rayleigh-Benard convection. We analyze results from direct simulation of an L/H = 4 aspect-ratio domain with periodic sidewalls at Ra = 1e5; 1e6; 1e7; 1e8 and at Pr = 1 by decomposing independent realizations into wind and fluctuations. It is shown that deep inside the thermal boundary layer, horizontal heat-fuxes exceed the average vertical heat-fux by a factor 3 due to the interaction between the wind and the mean temperature field. These large horizontal heat-fluxes are responsible for spatial temperature differences that drive the wind by creating pressure gradients. The wall fluxes and turbulent mixing in the bulk provide damping. Using the DNS results to parameterise the unclosed terms, a simple model capturing the essential processes governing the wind structure is derived. The model consists of two coupled differential equations for wind velocity and temperature amplitude. The equations indicate that the formation of a wind structure is inevitable due to the positive feedback resulting from the interaction between the wind and temperature field. Furthermore, the wind velocity is largely determined by the turbulence in the bulk rather than by the wall-shear stress. The model reproduces the Ra dependence of wind Reynolds number and temperature amplitude

A disturbance based control/structure design algorithm

Some authors take a classical approach to the simultaneous structure/control optimization by attempting to simultaneously minimize the weighted sum of the total mass and a quadratic form, subject to all of the structural and control constraints. Here, the optimization will be based on the dynamic response of a structure to an external unknown stochastic disturbance environment. Such a response to excitation approach is common to both the structural and control design phases, and hence represents a more natural control/structure optimization strategy than relying on artificial and vague control penalties. The design objective is to find the structure and controller of minimum mass such that all the prescribed constraints are satisfied. Two alternative solution algorithms are presented which have been applied to this problem. Each algorithm handles the optimization strategy and the imposition of the nonlinear constraints in a different manner. Two controller methodologies, and their effect on the solution algorithm, will be considered. These are full state feedback and direct output feedback, although the problem formulation is not restricted solely to these forms of controller. In fact, although full state feedback is a popular choice among researchers in this field (for reasons that will become apparent), its practical application is severely limited. The controller/structure interaction is inserted by the imposition of appropriate closed-loop constraints, such as closed-loop output response and control effort constraints. Numerical results will be obtained for a representative flexible structure model to illustrate the effectiveness of the solution algorithms

Attentive Learning of Sequential Handwriting Movements: A Neural Network Model

Defense Advanced research Projects Agency and the Office of Naval Research (N00014-95-1-0409, N00014-92-J-1309); National Science Foundation (IRI-97-20333); National Institutes of Health (I-R29-DC02952-01)

Modeling the growth of stylolites in sedimentary rocks

[1] Stylolites are ubiquitous pressure solution seams found in sedimentary rocks. Their morphology is shown to follow two self-affine regimes. Analyzing the scaling properties of their height over their average direction shows that (1) at small scale, they are self-affine surfaces with a Hurst exponent around 1, and (2) at large scale, they follow another self-affine scaling with Hurst exponent around 0.5. In the present paper, we show theoretically the influence of the main principal stress and the local geometry of the stylolitic interface on the dissolution reaction rate. We compute how it is affected by the deviation between the principal stress axis and the local interface between the rock and the soft material in the stylolite. The free energy entering in the dissolution reaction kinetics is expressed from the surface energy term and via integration from the stress perturbations due to these local misalignments. The resulting model shows the interface evolution at different stress conditions. In the stylolitic case, i.e., when the main principal stress is normal to the interface, two different stabilizing terms dominate at small and large scales which are linked respectively to the surface energy and to the elastic interactions. Integrating the presence of small-scale heterogeneities related to the rock properties of the grains in the model leads to the formulation of a Langevin equation predicting the dynamic evolution of the surface. This equation leads to saturated surfaces obeying the two observed scaling laws. Analytical and numerical analysis of this surface evolution model shows that the crossover length separating both scaling regimes depends directly on the applied far-field stress magnitude. This method gives the basis for the development of a paleostress magnitude marker. We apply the computation of this marker, i.e., the morphological analysis, on a stylolite found in the Dogger limestone layer located in the neighborhood of the ANDRA Underground Research Laboratory at Bure (eastern France). The results are consistent with the two scaling regimes expected, and the practical determination of the major principal paleostress, from the estimation of a crossover length, is illustrated on this example

Inertial Load Compensation by a Model Spinal Circuit During Single Joint Movement

Office of Naval Research (N00014-92-J-1309); CONACYT (Mexico) (63462