Robust Visual‐Servo Control of Robot Manipulators in the Presence of Uncertainty

This paper considers the problem of position control of planar robot manipulators via visual servoing in the presence of uncertainty associated with the robot mechanical dynamics and the camera system for both fixed‐camera and camera‐in‐hand configurations. Specifically, we first design a robust controller that compensates for uncertainty throughout the whole robot‐camera system and ensures global uniformly ultimately bounded position tracking for the fixed‐camera configuration. Under the same class of uncertainty, we then develop a setpoint controller for the camera‐in‐hand configuration that achieves global uniformly ultimately bounded regulation. Experimental results illustrating the performance of both controllers are also included. © 2003 Wiley Periodicals, Inc.     

Handwritten text separation from annotated machine printed documents using Markov Random Fields

The convenience of search, both on the personal computer hard disk as well as on the web, is still limited mainly to machine printed text documents and images because of the poor accuracy of handwriting recognizers. The focus of research in this paper is the segmentation of handwritten text and machine printed text from annotated documents sometimes referred to as the task of “ink separation” to advance the state-of-art in realizing search of hand-annotated documents. We propose a method which contains two main steps—patch level separation and pixel level separation. In the patch level separation step, the entire document is modeled as a Markov Random Field (MRF). Three different classes (machine printed text, handwritten text and overlapped text) are initially identified using G-means based classification followed by a MRF based relabeling procedure. A MRF based classification approach is then used to separate overlapped text into machine printed text and handwritten text using pixel level features forming the second step of the method. Experimental results on a set of machine-printed documents which have been annotated by multiple writers in an office/collaborative environment show that our method is robust and provides good text separation performance.     

Nonlinear tracking control of kinematically redundant robot manipulators

In this short paper, we consider the nonlinear control of kinematically redundant robot manipulators. Specifically, we use a Lyapunov technique to design a model-based nonlinear controller that achieves exponential link position and subtask tracking. We note that the control strategy does not require the computation of positional inverse kinematics and does not place any restriction on the self-motion of the manipulator; hence, the extra degrees of freedom are available for subtasks (i.e., maintaining manipulability, avoidance of mechanical limits and obstacle avoidance). Experimental implementations on a redundant robot are also included to illustrate the performance of the proposed control law.     

Adaptive position and orientation regulation for the camera‐in‐hand problem

This paper considers the camera‐space position and orientation regulation problem for the camera‐in‐hand problem via visual serving in the presence of parametric uncertainty associated with the robot dynamics and the camera system. Specifically, an adaptive robot controller is developed that forces the end‐effector of a robot manipulator to move such that the position and orientation of an object are regulated to a desired position and orientation in the camera‐space, despite parametric uncertainty throughout the entire robot‐camera system. An extension is also provided that illustrates how slight modifications can be made to the camera‐in‐hand control law to achieve adaptive position and orientation tracking of the end‐effector in the camera‐space for a fixed‐camera configuration. Simulation results are provided to illustrate the performance of the adaptive, camera‐in‐hand controller. © 2005 Wiley Periodicals, Inc.     

Autonomous detection of aerosolized biological agents by multiplexed immunoassay with polymerase chain reaction confirmation

The autonomous pathogen detection system (APDS) is an automated, podium-sized instrument that continuously monitors the air for biological threat agents (bacteria, viruses, and toxins). The system has been developed to warn of a biological attack in critical or high-traffic facilities and at special events. The APDS performs continuous aerosol collection, sample preparation, and detection using multiplexed immunoassay followed by confirmatory PCR using real-time TaqMan assays. We have integrated completely reusable flow-through devices that perform DNA extraction and PCR amplification. The fully integrated system was challenged with aerosolized Bacillus anthracis, Yersinia pestis, Bacillus globigii, and botulinum toxoid. By coupling highly selective antibody- and DNA-based assays, the probability of an APDS reporting a false positive is extremely low.     

A mixed finite element formulation for plate problems

A mixed triangular finite element model has been developed for plate bending problems in which effects of shear deformation are included. Linear distribution for all variables is assumed and the matrix equation is obtained through Reissner's variational principle. In this model, interelement compatibility is completely satisfied whereas the governing equations within the element are satisfied ‘in the mean’. A detailed error analysis is made and convergence of the scheme is proved. Numerical examples of thin and moderately thick plates are presented.