Design and Implementation of a Ubiquitous Robotic Space

This paper describes a concerted effort to design and implement a robotic service framework. The proposed framework is comprised of three conceptual spaces: physical, semantic, and virtual spaces, collectively referred to as a ubiquitous robotic space. We implemented a prototype robotic security application in an office environment, which confirmed that the proposed framework is an efficient tool for developing a robotic service employing IT infrastructure, particularly for integrating heterogeneous technologies and robotic platforms.     

Robotic Companions for Smart Space Interactions

In this piece we take a brief peek at the possible world of robotic companions. In such a world, robots are adopted as butlers in our homes, as baby watchers, as friends and in general as life companions. For example, Helen lives with a robotic companion named Schpuffy. In the morning, Schpuffy checks Helen's schedule and finds out she has an appointment with a neighbor to take a walk at 8:30 a.m. Schpuffy recognizes that it takes 30 minutes for her to prepare to go for a walk and wakes her up at 8:00 a.m. After she gets up, Schpuffy reminds Helen of her appointment at 8:30 a.m. While she gets dressed, Schpuffy lets her know that current weather is very cold and suggests that she wear thermal clothing. When she's about to leave the house, Schpuffy says "good bye" to her and locks the door as she leaves. Schpuffy hasn't gained majored acceptance. It's not in every home or even in a tiny fraction of homes. However, it's a bold new research that is taking shape with early commercial products already hitting the marketplace. It could soon be the chief appliance in your home, or the new interface technology for smart spaces.     

Adaptive fuzzy IMM algorithm for uncertain target tracking

In real system application, the interacting multiple model (IMM)-based uncertain target tracking system operates with the following problems: it requires less computing resources as well as a robust performance with respect to the maneuvering such as a sub-model mismatched case, and further, it requires an easy design procedure related to its structures and parameters. To solve these problems, an adaptive fuzzy IMM (AFIMM) algorithm, which is based on well-defined basis sub-models and well-adjusted mode transition probabilities (MTPs), is proposed. The basis sub-models are defined by the detailed analysis in terms of kinematic models as well as the maneuvering property and the MTPs are adjusted by the fuzzy adaptor as well as the fuzzy decision maker. To verify the performance of the proposed algorithm, an airborne target tracking is performed. Simulation results show that the AFIMM effectively solves the problems experienced in the uncertain target tracking system online. Keywords: Adaptive fuzzy IMM, basis sub-models, mode transition probabilities, uncertain target.     

Discrimination of visual and haptic rendering delays in networked environments

Many networked human-machine interface systems have a distributed structure for certain purposes such as more computational power, tele-presence, collaboration, and portability. However, network delays are inevitable in the distributed structure, and often make sensory information delivered behind time to the user. In the literature, the effect of network delays on the quality of information presentation has been considered with respect to task performances in most cases. In this paper, we pay attention to a more stringent criterion, namely whether perceptual artifacts caused by network delays are perceptible by the user. We examined minimum perceptible visual and/or haptic rendering delays by measuring their discrimination thresholds between normal and delayed virtual environments with and without a task, and report the results in this paper. We also provide a simple guideline for determining whether active delay compensation algorithms are required in a networked human-machine interface system by comparing representative network delays to the measured discrimination thresholds. Recommended by Guest Editor Phill Kyu Rhee. This work was supported in parts by a grant R01-2006-000-10808-0 and a NRL grant R0A-2008-000-20087-0 both from KOSEF and by a ITRC support program C1090-0804-0002 from IITA, all funded by the Korea government. In Lee is a Ph.D student in Computer Science and Engineering at POSTECH, of Korea. He received the B.S. degree in Information and Communication Engineering from Sungkyunkwan University in 2006. His research interests include haptics, virtual reality, and human-computer interaction. Seungmoon Choi is an Assistant Professor in Computer Science and engineering at POSTECH, Korea. He received the B.S. and M.S. degrees in Control and Instrumentation Engineering from Seoul National University in 1995 and 1997, respectively, and the Ph.D. degree in Electrical and Computer Engineering from Purdue University in 2003. His research areas include haptics, virtual reality, data perceptualization, and applied perception.     

Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects. Recommended by Editorial Board member Hyo-Choong Bang under the direction of Editor Hyun Seok Yang. This work was supported by the Korea Research Foundation Grant (MOEHRD) KRF-2005-204-D00002, the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government(MOST) R0A-2007-000-10017-0 and Engineering Research Institute at Seoul National University. Daewon Lee received the B.S. degree in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical and Aerospace Engineering. He has been a member of the UAV research team at SNU since 2005. His research interests include applications of nonlinear control and vision-based control of UAV. H. Jin Kim received the B.S. degree from Korea Advanced Institute of Technology (KAIST) in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from University of California, Berkeley in 1999 and 2001, respectively. From 2002–2004, she was a Postdoctoral Researcher and Lecturer in Electrical Engineering and Computer Science (EECS), University of California, Berkeley (UC Berkeley). From 2004–2009, she was an Assistant Professor in the School of in Mechanical and Aerospace Engineering at Seoul National University (SNU), Seoul, Korea, where she is currently an Associate Professor. Her research interests include applications of nonlinear control theory and artificial intelligence for robotics, motion planning algorithms. Shankar Sastry received the B.Tech. degree from the Indian Institute of Technology, Bombay, in 1977, and the M.S. degree in EECS, the M.A. degree in mathematics, and the Ph.D. degree in EECS from UC Berkeley, in 1979, 1980, and 1981, respectively. He is currently Dean of the College of Engineering at UC Berkeley. He was formerly the Director of the Center for Information Technology Research in the Interest of Society (CITRIS). He served as Chair of the EECS Department from January, 2001 through June 2004. In 2000, he served as Director of the Information Technology Office at DARPA. From 1996 to 1999, he was the Director of the Electronics Research Laboratory at Berkeley (an organized research unit on the Berkeley campus conducting research in computer sciences and all aspects of electrical engineering). He is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences and holds faculty appointments in the Departments of Bioengineering, EECS and Mechanical Engineering. Prior to joining the EECS faculty in 1983 he was a Professor with the Massachusetts Institute of Technology (MIT), Cambridge. He is a member of the National Academy of Engineering and Fellow of the IEEE.     

MEMS-based gas flow sensors

Micro-electro-mechanical system (MEMS) devices integrate various mechanical elements, sensors, actuators, and electronics on a single silicon substrate in order to accomplish a multitude of different tasks in a diverse range of fields. The potential for device miniaturization made possible by MEMS micro-fabrication techniques has facilitated the development of many new applications, such as highly compact, non-invasive pressure sensors, accelerometers, gas sensors, etc. Besides their small physical footprint, such devices possess many other advantages compared to their macro-scale counterparts, including greater precision, lower power consumption, more rapid response, and the potential for low-cost batch production. One area in which MEMS technology has attracted particular attention is that of flow measurement. Broadly speaking, existing micro-flow sensors can be categorized as either thermal or non-thermal, depending upon their mode of operation. This paper commences by providing a high level overview of the MEMS field and then describes some of the fundamental thermal and non-thermal micro-flow sensors presented in the literature over the past 30 years or so.     

Application of maximum entropy principle for reliability-based design optimization

The maximum entropy principle (MEP) is used to generate a natural probability distribution among the many possible that have the same moment conditions. The MEP can accommodate higher order moment information and therefore facilitate a higher quality PDF model. The performance of the MEP for PDF estimation is studied by using more than four moments. For the case with four moments, the results are compared with those by the Pearson system. It is observed that as accommodating higher order moment, the estimated PDF converges to the original one. A sensitivity analysis formulation of the failure probability based on the MEP is derived for reliability-based design optimization (RBDO) and the accuracy is compared with that by finite difference method (FDM). Two RBDO examples including a realistic three-dimensional wing design are solved by using the derived sensitivity formula and the MEP-based moment method. The results are compared with other methods such as TR-SQP, FAMM + Pearson system, FFMM + Pearson system in terms of accuracy and efficiency. It is also shown that an improvement in the accuracy by including more moment terms can increase numerical efficiency of optimization for the three-dimensional wing design. The moment method equipped with the MEP is found flexible and well adoptable for reliability analysis and design.     

Extraction of genomic DNA and detection of single nucleotide polymorphism genotyping utilizing an integrated magnetic bead-based microfluidic platform

This study presents a new magnetic bead-based microfluidic platform, which integrates three major modules for rapid leukocytes purification, genomic DNA (gDNA) extraction and fast analysis of genetic gene. By utilizing microfluidic technologies and magnetic beads conjugated with CD_15/45 antibodies, leukocytes in a human whole blood sample can be first purified and concentrated, followed by extraction of gDNA utilizing surface-charge switchable, DNA-specific, magnetic beads in the lysis solution. Then, specific genes associated with genetic diseases can be amplified by an on-chip polymerase chain reaction (PCR) process automatically. The whole pretreatment process including the leukocytes purification and gDNA extraction can be performed in an automatic fashion with the incorporation of the built bio-separators consisting of microcoils array within less than 20 min. The detection of single nucleotide polymorphism (SNP) genotyping of methylenetetra-hydrofolate reductase (MTHFR) C677T region associated with an increased risk of genetic diseases was further performed to demonstrate the capability of the proposed system. The extracted gDNA can be transported into a micro PCR chamber for on-chip fast nucleic acid amplification of detection genes with minimum human intervention. Hence, the developed system may provide a powerful automated platform for pretreatment of human leukocytes, gDNA extraction and fast analysis of genetic gene.     

Rate control algorithm based on intra-picture complexity for H.264/AVC

An efficient rate control algorithm based on the content-adaptive initial quantisation parameter (QP) setting scheme and the peak signal-to-noise ratio (PSNR) variation-limited bit-allocation strategy for lowcomplexity mobile applications is presented. This algorithm can efficiently measure the residual complexity of intra-pictures without performing the computation-intensive intra-prediction and mode decision in H.264/AVC, based on the structural and statistical features of local textures. This can adaptively set proper initial QP values for versatile video contents. In addition, this bit-allocation strategy can effectively distribute bit-rate budgets based on the monotonic property to enhance overall coding efficiency while maintaining the consistency of visual quality by limiting the variation of quantisation distortion. The experimental results reveal that the proposed algorithm surpasses the conventional rate control approaches in terms of the average PSNR from 0.34 to 0.95 dB. Moreover, this algorithm provides more impressive visual quality and more robust buffer controllability when compared with other algorithms.