Hierarchical control of multiple resources in distributed real-time and embedded systems

Real-time and embedded systems have traditionally been designed for closed environments where operating conditions, input workloads, and resource availability are known a priori, and are subject to little or no change at runtime. There is increasing demand, however, for adaptive capabilities in distributed real-time and embedded (DRE) systems that execute in open environments where system operational conditions, input workload, and resource availability cannot be characterized accurately a priori. A challenging problem faced by researchers and developers of such systems is devising effective adaptive resource management strategies that can meet end-to-end quality of service (QoS) requirements of applications. To address key resource management challenges of open DRE systems, this paper presents the Hierarchical Distributed Resource-management Architecture (HiDRA), which provides adaptive resource management using control techniques that adapt to workload fluctuations and resource availability for both bandwidth and processor utilization simultaneously. This paper presents three contributions to research in adaptive resource management for DRE systems. First, we describe the structure and functionality of HiDRA. Second, we present an analytical model of HiDRA that formalizes its control-theoretic behavior and presents analytical assurance of system performance. Third, we evaluate the performance of HiDRA via experiments on a representative DRE system that performs real-time distributed target tracking. Our analytical and empirical results indicate that HiDRA yields predictable, stable, and efficient system performance, even in the face of changing workload and resource availability.     

MRI-based Sensors for In Vivo Imaging of Metal Ions in Biology

Although much is known about the diverse roles of metal ions in biology, most of the acquired knowledge was obtained with fluorescent dyes or electrophysiological approaches. However, the ability to non-invasively monitor variation in metal ions and to assess their physiological distribution in health and disease is very limited. Recent advances in the field of molecular magnetic resonance imaging (MRI) have offered new capabilities through the design and development of MRI-responsive sensors for a wide range of applications, including the ability to sense and spatially map metal ions. Here, we briefly summarize the recent progress in the development and performance of MRI sensors designed to monitor metal ions in biology while emphasizing their in vivo uses, their limitations, and remaining challenges. Among the proposed MRI-sensors, Zn²⁺ and Ca²⁺ responsive agents are those that have already been used in live intact subjects, and therefore, these will be emphasized here.     

Data-efficient learning of robotic clothing assistance using Bayesian Gaussian process latent variable model

ABSTRACT

Motor-skill learning for complex robotic tasks is a challenging problem due to the high task variability. Robotic clothing assistance is one such challenging problem that can greatly improve the quality-of-life for the elderly and disabled. In this study, we propose a data-efficient representation to encode task-specific motor-skills of the robot using Bayesian nonparametric latent variable models. The effectivity of the proposed motor-skill representation is demonstrated in two ways: (1) through a real-time controller that can be used as a tool for learning from demonstration to impart novel skills to the robot and (2) by demonstrating that policy search reinforcement learning in such a task-specific latent space outperforms learning in the high-dimensional joint configuration space of the robot. We implement our proposed framework in a practical setting with a dual-arm robot performing clothing assistance tasks.     

Generalized coating route to silica and titania films with orthogonally tilted cylindrical nanopore arrays

We describe a simple, inexpensive coating method to produce thin silica and titania films with surfactant templated, orthogonally tilted cylindrical nanopore arrays. These films can be deposited onto any substrate because orientation of the 2D hexagonally close packed (HCP) mesophases out of the plane of the film is directed by a chemically neutral sacrificial copolymer layer. Orientation of the HCP mesophases through the entire thickness of films cured in open air is achieved by limiting the coating thickness. This generalizes the coating method by making it possible to deposit oriented films on substrates of any curvature and size. We find a critical thickness between 70 and 100 nm, below which the triblock copolymer surfactant-templated HCP phase aligns completely out of the plane of glass and silicon wafer substrates. Above this thickness, the effect of the chemically neutral bottom layer does not propagate across the entire film, and alignment of the HCP mesophases parallel to the (nonpolar) air interface produces a mixed orientation.     

The effect of Knudsen layers on rarefied cylindrical Couette gas flows

We investigate a power-law probability distribution function to describe the mean free path of rarefied gas molecules in non-planar geometries. A new curvature-dependent model is derived by taking into account the boundary-limiting effects on the molecular mean free path for surfaces with both convex and concave curvatures. The Navier–Stokes constitutive relations and the velocity-slip boundary conditions are then modified based on this power-law scaling through the transport property expressions in terms of the mean free path. Velocity profiles for isothermal cylindrical Couette flow are obtained using this power-law model and compared with direct simulation Monte Carlo (DSMC) data. We demonstrate that our model is more accurate than the classical slip solution, and we are able to capture important non-linear trends associated with the non-equilibrium physics of the Knudsen layer. In addition, we establish a new criterion for the critical accommodation coefficient that leads to the non-intuitive phenomenon of velocity inversion. The power-law model predicts that the critical accommodation coefficient is significantly lower than that calculated using the classical slip solution, and is in good agreement with available DSMC data. Our proposed constitutive scaling for non-planar surfaces is based on simple physical arguments and can be readily implemented in conventional fluid dynamics codes for arbitrary geometric configurations of microfluidic systems.     

Adaptive motion generation using imitation learning and highly compliant end effector for autonomous cleaning

Recent demographic trends in super aging societies, such as Japan, is leading to severe worker shortage. Service robots can play a promising role to augment human workers for performing various household and assistive tasks. Toilet cleanup is one such challenging task that involves performing complaint motion planning in a constrained toilet setting. In this study, we propose an end-to-end robotic framework to perform various tasks related to toilet cleanup. Our key contributions include the design of a complaint and multipurpose end-effector, an adaptive motion generation algorithm, and an autonomous mobile manipulator capable of garbage detection, garbage disposal and liquid removal. We evaluate the performance of our framework with the competition setting used for toilet cleanup in the Future Convenience Store Challenge at the World Robot Summit 2018. We demonstrate that our proposed framework is capable of successfully completing all the tasks of the competition within the time limit.     

Analytical solution of plane Poiseuille flow within Burnett hydrodynamics

In the current paper, low-speed isothermal microscale gas flows have been investigated utilizing the augmented Burnett equations. There has been limited success to analytically solve the Burnett equations till date. We propose an analytical solution to Burnett equations, which is shown to satisfy the full set of augmented Burnett equations up to Kn of 2.2 with an error of 1 %. Detailed validation shows that the solution represents the integral flow parameters accurately up to Kn ~ 2.2 and local field properties up to Kn ~ 0.5. The range over which the proposed Burnett analytical solution is applicable is substantially better than existing analytical solutions, without incorporating any wall scaling functions into constitutive relations and variation of slip coefficients in the boundary conditions. Normalized mass flow rate, friction factor, and axial velocity profile results show very good agreement with the experimental and simulation data. The analytical solution is also able to predict the change in the curvature of streamwise pressure profile.