Extraction and implementation of muscle synergies in neuro-mechanical control of upper limb movement

This work faces the redundancy problem, a central concern in robotics, in a particular force-producing task by using muscle synergies to simplify the control. We extracted muscle synergies from human electromyograph signals and interpreted the physical meaning of the identified muscle synergies. Based on the human analysis results, we hypothesized a novel control framework that can explain the mechanism of the human motor control. The framework was tested in controlling a pneumatic-driven robotic arm to perform a reaching task. This control method, which uses only two synergies as manipulated variables for driving antagonistic pneumatic artificial muscles to generate desired movements, would be useful to deal with the redundancy problem; thus, suggesting a simple but efficient control for human-like robots to work safely and compliantly with humans.     

Effect of viscosities of dispersed and continuous phases in microchannel oil-in-water emulsification

Although many aspects of microchannel emulsification have been covered in literature, one major uncharted area is the effect of viscosity of both phases on droplet size in the stable droplet generation regime. It is expected that for droplet formation to take place, the inflow of the continuous phase should be sufficiently fast compared to the outflow of the liquid that is forming the droplet. The ratio of the viscosities was therefore varied by using a range of continuous and dispersed phases, both experimentally and computationally. At high viscosity ratio (η _d/η _c), the droplet size is constant; the inflow of the continuous phase is fast compared to the outflow of the dispersed phase. At lower ratios, the droplet diameter increases, until a viscosity ratio is reached at which droplet formation is no longer possible (the minimal ratio). This was confirmed and elucidated through CFD simulations. The limiting value is shown to be a function of the microchannel design, and this should be adapted to the viscosity of the two fluids that need to be emulsified.     

Stochastic model predictive braking control for heavy-duty commercial vehicles during uncertain brake pressure and road profile conditions

When heavy-duty commercial vehicles (HDCVs) must engage in emergency braking, uncertain conditions such as the brakepressure and road profile variations will inevitably affect braking control. To minimize these uncertainties, we propose acombined longitudinal and lateral controller method based on stochastic model predictive control (SMPC) that is achieved viaChebyshev–Cantelli inequality. In our method, SMPC calculates braking control inputs based on a finite time prediction thatis achieved by solving stochastic programming elements, including chance constraints. To accomplish this, SMPC explicitlydescribes the probabilistic uncertainties to be used when designing a robust control strategy. The main contribution of thispaper is the proposal of a braking control formulation that is robust against probabilistic friction circle uncertainty effects.More specifically, the use of Chebyshev–Cantelli inequality suppresses road profile influences, which have characteristicsthat are different from the Gaussian distribution, thereby improving both braking robustness and control performance againststatistical disturbances.Additionally, since theKalman filtering (KF) algorithm is used to obtain the expectation and covarianceused for calculating deterministic transformed chance constraints, the SMPC is reformulated as a KF embedded deterministicMPC. Herein, the effectiveness of our proposed method is verified via a MATLAB/Simulink and TruckSim co-simulation.     

Hyper least squares fitting of circles and ellipses

This work extends the circle fitting method of Rangarajan and Kanatani (2009) to accommodate ellipse fitting. Our method, which we call HyperLS, relies on algebraic distance minimization with a carefully chosen scale normalization. The normalization is derived using a rigorous error analysis of least squares (LS) estimators so that statistical bias is eliminated up to second order noise terms. Numerical evidence suggests that the proposed HyperLS estimator is far superior to the standard LS and is slightly better than the Taubin estimator. Although suboptimal in comparison to maximum likelihood (ML), our HyperLS does not require iterations. Hence, it does not suffer from convergence issues due to poor initialization, which is inherent in ML estimators. In this sense, the proposed HyperLS is a perfect candidate for initializing the ML iterations.     

Functional un|unparsing

Danvy??s functional unparsing problem (Danvy in J. Funct. Program. 8(6), 621?C625, 1998) is to implement a type-safe ??printf?? function, which converts a sequence of heterogeneous arguments to a string according to a given format. The dual problem is to implement a type-safe ??scanf?? function, which extracts a sequence of heterogeneous arguments from a string by interpreting (Friedman and Wand in LFP, pp. 348?C355, 1984 and in Essentials of Programming Languages, MIT Press, 2008) the same format as an equally heterogeneous sequence of patterns that binds zero or more variables. We derive multiple solutions to both problems (Wand in J. ACM 27(1), 164?C180, 1980) from their formal specifications (Wand in Theor. Comput. Sci. 20(1), 3?C32, 1982). On one hand, our solutions show how the Hindley-Milner type system, unextended, permits accessing heterogeneous sequences with the static assurance of type safety. On the other hand, our solutions demonstrate the use of control operators (Felleisen et al. in Proceedings of the 1988 ACM Conference on Lisp and Functional Programming, pp. 52?C62, ACM Press, New York, 1988; Wand in POPL 85: Conference Record of the Annual ACM Symposium on Principles of Programming Languages, vol. 16, ACM Press, New York, 1985; Meyer and Wand in Logics of Programs, Lecture Notes in Computer Science, vol. 193, pp. 219?C224, Springer, Berlin, 1985) to communicate with formats as coroutines (Wand in Proceedings of the 1980 ACM Conference on Lisp and Functional Programming, vol. 12, pp. 285?C299, ACM Press, New York, 1980 and Haynes et al. in LFP, pp. 293?C298, 1984).     

Translational lemmas for DLOGTIME-uniform circuits,alternating TMs,and PRAMs

We present translational lemmas for the three standard models of parallel computation, and apply them to obtain tight hierarchy results. It is shown that, for arbitrarily small rational constant , (i) there is a language which can be accepted by a -uniform circuit family of depth and size but not by any -uniform circuit family of depth and size , (ii) there is a language which can be accepted by a -time -space ATM with l worktapes but not by any -time -space ATM with the same l worktapes if the number of tape symbols is fixed, and (iii) there is a language which can be accepted by a -time PRAM with processors but not by any -time PRAM with processors. Here, c > 0, d ≥ 1, r ₁ > 1, and r ₂ ≥ 1 are arbitrary rational constants, and l ≥ 2 is an arbitrary integer. Preliminary versions of different parts of this paper appeared in Proc. MCU 2004 (LNCS 3354) and Proc. FCT 2005 (LNCS 3623).     

High-performance cone beam reconstruction using CUDA compatible GPUs

Compute unified device architecture (CUDA) is a software development platform that allows us to run C-like programs on the nVIDIA graphics processing unit (GPU). This paper presents an acceleration method for cone beam reconstruction using CUDA compatible GPUs. The proposed method accelerates the Feldkamp, Davis, and Kress (FDK) algorithm using three techniques: (1) off-chip memory access reduction for saving the memory bandwidth; (2) loop unrolling for hiding the memory latency; and (3) multithreading for exploiting multiple GPUs. We describe how these techniques can be incorporated into the reconstruction code. We also show an analytical model to understand the reconstruction performance on multi-GPU environments. Experimental results show that the proposed method runs at 83% of the theoretical memory bandwidth, achieving a throughput of 64.3 projections per second (pps) for reconstruction of 512³-voxel volume from 360 512²-pixel projections. This performance is 41% higher than the previous CUDA-based method and is 24 times faster than a CPU-based method optimized by vector intrinsics. Some detailed analyses are also presented to understand how effectively the acceleration techniques increase the reconstruction performance of a naive method. We also demonstrate out-of-core reconstruction for large-scale datasets, up to 1024³-voxel volume.     

Wearable vibrotactile systems for virtual contact and information display

This paper presents a development history of a wearable, scalable vibrotactile stimulus delivery system. This history has followed a path from desktop-based, fully wired systems, through hybrid approaches consisting of a wireless connection from the host computer to a body-worn control box and wires to each tactor, to a completely wireless system employing Bluetooth technology to connect directly from the host to each individual tactor unit. Applications for such a system include delivering vibrotactile contact cues to users of virtual environments, providing directional cues in order to increase situational awareness in both real and virtual environments, and for general information display in wearable contexts. Through empirical study, we show that even a simple configuration, such as eight tactors arrayed around the torso, can be effective in increasing situational awareness in a building-clearing task, compared to users who perform the same task without the added cues.     

Face relighting using discriminative 2D spherical spaces for face recognition

As part of the face recognition task in a robust security system, we propose a novel approach for the illumination recovery of faces with cast shadows and specularities. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients by using the face spherical spaces properties. First, an illumination training database is generated by computing the properties of the spherical spaces out of face albedo and normal values estimated from 2D training images. The training database is then discriminately divided into two directions in terms of the illumination quality and light direction of each image. Based on the generated multi-level illumination discriminative training space, we analyze the target face pixels and compare them with the appropriate training subspace using pre-generated tiles. When designing the framework, practical real-time processing speed and small image size were considered. In contrast to other approaches, our technique requires neither 3D face models nor restricted illumination conditions for the training process. Furthermore, the proposed approach uses one single face image to estimate the face albedo and face spherical spaces. In this work, we also provide the results of a series of experiments performed on publicly available databases to show the significant improvements in the face recognition rates.     

Straight-through microchannel devices for generating monodisperse emulsion droplets several microns in size

The authors recently proposed a promising technique for producing monodisperse emulsions using a straight-through microchannel (MC) device composed of an array of microfabricated oblong holes. This research developed new straight-through MC devices with tens of thousands of oblong channels of several microns in size on a silicon-on-insulator plate, and investigated the emulsification characteristics using the microfabricated straight-through MC devices. Monodisperse oil-in-water (O/W) and W/O emulsions with average droplet diameters of 4.4–9.8 μm and coefficients of variation of less than 6% were stably produced using surface-treated straight-through MC devices that included uniformly sized oblong channels with equivalent diameters of 1.7–5.4 μm. The droplet size of the resultant emulsions depended greatly on the size of the preceding oblong channels. The emulsification process using the straight-through MC devices developed in this research had very high apparent energy efficiencies of 47–60%, defined as (actual energy input applied to droplet generation/theoretical minimum energy input necessary for making droplets) × 100. Straight-through MC devices with numerous oblong microfluidic channels also have great potential for increasing the productivity of monodisperse fine emulsions.