Visual Pattern Recognition Models for Remote Sensing of Civil Infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Electrotactile touch surface by using transparent graphene

In this work we present a flexible Electrostatic Tactile (ET) surface/display realized by using new emerging material graphene. The graphene is transparent conductor which successfully replaces previous solution based on indium-thin oxide (ITO) and delivers more reliable solution for flexible and bendable displays. The electrostatic tactile surface is capable of delivering programmable, location specific tactile textures. The ET device has an area of 25 cm 2, and consists of 130 μm thin optically transparent (>76%) and mechanically flexible structure overlaid unobtrusively on top of a display. The ET system exploits electro vibration phenomena to enable on-demand control of the frictional force between the user's fingertip and the device surface. The ET device is integrated through a controller on a mobile display platform to generate fully programmable range of stimulating signals. The ET haptic feedback is formed in accordance with the visual information displayed underneath, with the magnitude and pattern of the frictional force correlated with both the images and the coordinates of the actual touch in real time forming virtual textures on the display surface (haptic virtual silhouette). To quantify rate of change in friction force we performed a dynamic friction coefficient measurement with a system involving an artificial finger mimicking the actual touch. During operation, the dynamic friction between the ET surface and an artificial finger stimulation increases by 26% when the load is 0.8 N and by 24% when the load is 1 N. © 2012 ACM.

Dynamic programming solutions for decentralized state-feedback LQG problems with communication delays

This paper presents explicit solutions for a class of decentralized LQG problems in which players communicate their states with delays. A method for decomposing the Bellman equation into a hierarchy of independent subproblems is introduced. Using this decomposition, all of the gains for the optimal controller are computed from the solution of a single algebraic Riccati equation. © 2012 AACC American Automatic Control Council).

On the structure of state-feedback LQG controllers for distributed systems with communication delays

This paper presents explicit solutions for a few distributed LQG problems in which players communicate their states with delays. The resulting control structure is reminiscent of a simple management hierarchy, in which a top level input is modified by newer, more localized information as it gets passed down the chain of command. It is hoped that the controller forms arising through optimization may lend insight into the control strategies of biological and social systems with communication delays. © 2011 IEEE.

A neuro-inspired method for data rate limited feedback control

The nervous system implements a networked control system in which the plants take the form of limbs, the controller is the brain, and neurons form the communication channels. Unlike standard networked control architectures, there is no periodic sampling, and the fundamental units of communication contain little numerical information. This paper describes a novel communication channel, modeled after spiking neurons, in which the transmitter integrates an input signal and sends out a spike when the integral reaches a threshold value. The reciever then filters the sequence of spikes to approximately reconstruct the input signal. It is shown that for appropriate choices of channel parameters, stable feedback control over these spiking channels is possible. Furthermore, good tracking performance can be achieved. The data rate of the channel increases linearly with the size of the inputs. Thus, when placed in a feedback loop, small loop gains imply a low data rate. ©2010 IEEE.