Serge N. Demidenko

Master-Slave Control of a Teleoperated Anthropomorphic Robotic Arm with Gripping Force Sensing

This paper details methods of solving problems that are encountered when human beings teleoperate robots. Special emphasis has been given to the ease of operation and some form of force sensation. Through the use of a rigid control rig, fitted to the users arm, it is possible to easily control an anthropomorphic robot arm using a master-slave control methodology. The force being exerted by the arm is measured and fed back to the user who is operating the master unit

Wireless Sensor Network for Selective Activity Monitoring In a Home for the Elderly

In this paper we present the design intricacies and implementation details of a novel selective activity monitoring (SAM) system targeted for homes for the elderly. The system is designed to support people who wish to live alone but, because of old age, ill health or disability, there is some risk in this, which worries their family or friends. The system works on the principle of using sensor units (SU) to monitor the appliance throughout a house and detect when certain desired electrical equipments are turned on. Rules are defined for appliances to turn on in certain time intervals. The rules are flexible and can be user-defined based on the daily activities of a person. Several levels of alarm conditions have been created based on combination of rules that are violated. Any number of sensor units may be installed in a house, one each to monitor an electrical appliance. A central controller unit (CCU) queries the sensor units and logs the data into a PC at a pre-defined rate. Communication between the SUs and the controller is using radio-frequency wireless media. The rules inference engine runs on the PC and whenever the situation requires, sends a text message to the care-givers or relatives. Since no vision sensors (camera or infrared) are used, the system is non-invasive, respects privacy and has found wide acceptance. The system is completely customizable, allowing the user to select which appliances to monitor and define exactly what is classified as unusual behavior.

A low-cost sensing system for quality monitoring of dairy products

The dairy industry is in need of a cost-effective, highly reliable, very accurate, and fast measurement system to monitor the quality of dairy products. This paper describes the design and fabrication works undertaken to develop such a system. The techniques used center around planar electromagnetic sensors operating with radio frequency excitation. Computer-aided computation, being fast, facilitates on-line monitoring of the quality. The sensor technology proposed has the ability to perform volumetric penetrative measurements to measure properties throughout the bulk of the product.

RAM diagnostic tests

In this paper the following problems are considered : 1) march tests diagnostic capability estimation, ie. the type of the fault and its location; 2) advanced march tests with diagnostic ability; 3) a march test with the same fault coverage as test March C and optimal diagnostic ability.

Reducing burn-in time through high-voltage stress test and Weibull statistical analysis

To guarantee an industry standard of reliability in ICs, manufacturers incorporate special testing techniques into the circuit manufacturing process. For most electronic devices, the specific reliability required is quite high, often producing a lifespan of several years. Testing such devices for reliability under normal operating conditions would require a very long period of time to gather the data necessary for modeling the devices failure characteristics. Under this scenario, a device might become obsolete by the time the manufacturer could guarantee its reliability. High-voltage stress testing (HVST) is common in IC manufacturing, but publications comparing it with other test and burn-in methods are scarce. This article shows that the use of HVST can dramatically reduce the amount of required burn-in.

Saxophone Reed Inspection Employing Planar Electromagnetic Sensors

This paper deals with the research and development of a prototype of a planar electromagnetic sensor for use in nondestructive evaluation (NDE) of saxophone reeds. Analytical modeling and experimental research have been employed, leading to very promising results that could serve as a starting point for development of a commercial-grade sensor. In addition to the reed testing, the sensor could have wide applications in NDE and testing of several other products such as meat, dairy products, etc.

Real-time identification and predictive control of fast mobile robots using global vision sensing

This paper presents a predictive controller for intercepting mobile targets. A global vision system is used to identify fast moving objects and uses a color threshold technique to calculate their position and orientation. The inherent systemic noise in the raw sensor data, as well as vision quantization noise, is smoothed using Kalman filtering before being fed to the controller, and it is shown that this leads to superior accuracy of the controller. The predictive controller is based on the state transition-based control (STBC) technique. As a case study, STBC has been applied to a goalkeepers behavior in robot soccer which includes interception and clearance of ball. Further evaluation of the controller has been done for shooting the ball toward a target position. The system is examined for both stationary and moving objects. It is shown that predictive filtering of rough sensor data is essential to increase the reliability and accuracy of detection, and thus interception, of fast moving objects.

March PS(23N) test for DRAM pattern-sensitive faults

March algorithms are widely used in DRAM testing. They are relatively simple yet providing high fault coverage especially with respect to stuck-at faults, address uniqueness faults, and some types of cell-interaction faults. At the same time the capability of traditional March tests to detect pattern-sensitive faults is rather limited. This paper proposes an approach to enhance March test detection capability with respect to the pattern-sensitive faults.

Gaussian Process Dynamical Models for hand gesture interpretation in Sign Language

Classifying human hand gestures in the context of a Sign Language has been historically dominated by Artificial Neural Networks and Hidden Markov Model with varying degrees of success. The main objective of this paper is to introduce Gaussian Process Dynamical Model as an alternative machine learning method for hand gesture interpretation in Sign Language. In support of this proposition, the paper presents the experimental results for Gaussian Process Dynamical Model against a database of 66 hand gestures from the Malaysian Sign Language. Furthermore, the Gaussian Process Dynamical Model is tested against established Hidden Markov Model for a comparative evaluation. A discussion on why Gaussian Process Dynamical Model is superior over existing methods in Sign Language interpretation task is then presented.

Hough Transform Run Length Encoding for Real-Time Image Processing

This paper introduces a real-time image processing algorithm based on run length encoding (RLE) for a vision based intelligent controller of a humanoid robot system. The RLE algorithms identify objects in the image providing their size and position. A RLE Hough transform is also presented for recognition of landmarks in the image to aid robot localization. The vision system presented has been tested by simulating the dynamics of the robot system as well as the image processing subsystem. The real-time image processing and control algorithms allow the unstable dynamic model of the biped robot to be controlled