Design of a simulation environment for laboratory management by robot organizations

This paper describes the basic concepts needed for a simulation environment capable of supporting the design of robot organizations for managing chemical, or similar, laboratories on the planned U.S. Space Station. The environment should facilitate a thorough study of the problems to be encountered in assigning the responsibility of managing a non-life-critical, but mission valuable, process to an organized group of robots. In the first phase of the work, we seek to employ the simulation environment to develop robot cognitive systems and strategies for effective multi-robot management of chemical experiments. Later phases will explore human-robot interaction and development of robot autonomy

Tworzenie programu badawczego na amerykańskiej uczelni: skuteczne strategie

This informational article discusses opportunities and strategies for how to develop an externally funded research program in the American academic environment, specifically in STE M (science, technology, engineering, and mathematics) disciplines. It is presented from a long-term perspective of a faculty member with active research, who has served in all ranks (assistant, associate, and full professor) and has led a large academic department at the University of Arizona for several years. It is stipulated that the employment offer for a junior faculty include an adequate start-up package which allows to set the research program in motion by establishing a laboratory and hiring graduate students. The spectrum of funding sources for STE M research is given with a brief annotation of the current funding climate and mechanisms in the USA. As junior faculty face negative submission outcomes, strong encouragement and pragmatic advice is needed so that faculty can focus their efforts, persist in grant competitions, and ultimately succeed. Grant planning and submission suggestions that might help in this process and lead to good outcomes are given. The article concludes with the stipulation that faculty maintain high standards of academic integrity, ethics, and quality and not succumb to potentially perverse incentives to pursue funds just for the sake of generating higher quantitative indicators of their productivity.Niniejszy artykuł opisuje możliwości i strategie tworzenia programów badawczych z zewnętrznym finansowaniem na amerykańskich uczelniach w dziedzinach ścisłych (nauki przyrodnicze, technologia, inżynieria oraz matematyka). Artykuł jest napisany z perspektywy wieloletniego pracownika naukowego, który prowadzi badania i przeszedł przez wszystkie szczeble kariery naukowej (asystent, profesor nadzwyczajny i profesor zwyczajny) oraz przez kilka lat stał na czele dużego wydziału na University of Arizona. Propozycja umowy zatrudnienia dla młodszego członka kadry naukowej powinna zawierać odpowiedni pakiet początkowy, który umożliwia rozpoczęcie programu badawczego przez otwarcie laboratorium i zatrudnienie laborantów spośród studentów. Spektrum źródeł finansowania badań w zakresie nauk ścisłych jest opisane wraz z krótką wzmianką o obecnym klimacie finansowym i mechanizmach finansowania w USA. Ponieważ młodszy członek kadry naukowej zmierzy się niejednokrotnie z odmową przyznania środków, będzie potrzebować zachęty oraz pragmatycznych porad, które pomogą skupić wysiłki, wytrwać i nadal startować w konkursach dotacyjnych, co ostatecznie zaowocuje uzyskaniem finansowania. Niniejszy artykuł zwiera również sugestie, jak planować granty i składać wnioski. Na zakończenie autor wnosi o to, żeby kadra naukowa zachowała wysokie standardy akademickiej uczciwości, etyki i jakości oraz nie ulegała pokusie pozyskiwania środków finansowych jedynie w celu generowania wyższych wskaźników swojej produktywności

An Adaptive Force Guidance System for Computer-Guided Laparoscopy Training

We present an adaptive force guidance system for laparoscopic surgery skills training. This system consists of self-adjusting fuzzy sliding-mode controllers and switching mode controllers to provide proper force feedback. Using virtual fixtures, the proposed system restricts motions or guides a trainee to navigate a surgical instrument in a 3-D space in a manner that mimics a human instructor who would teach the trainees by holding their hands. The self-adjusting controllers incorporate human factors, such as different force sensitivity and proficiency levels. The proposed system was implemented and evaluated using the computer-assisted surgical trainer (CAST). The effects of the force guidance system are presented based on the experimental test results.National Science FoundationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Monocular Depth Estimation using Synthetic Data for an Augmented Reality Training System in Laparoscopic Surgery

Depth estimation is an important challenge in the field of augmented reality. Supervised deep learning methods of depth estimation can be difficult to use in novel settings due to the need for labeled training data. The work presented in this paper overcomes the challenge in a laparoscopic surgical simulation environment by using synthetic data generation for RGB-D training data. We also provide a neural network architecture that can generate real-time 448x448 depth map outputs suitable for use in AR applications. Our approach shows satisfactory performance when tested on a non-synthetic test dataset with an RMSE of 2.50 cm, MAE of 1.04 cm, and δ < 1.25 of 0.987.National Science FoundationImmediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Decision of Learning Status Based on Modeling of the Information Measurement of Social Behavioral Tasks in Rhesus Monkeys

We are interested in identifying the learning status of the social behavioral tasks in the rhesus monkey. In addition, we define the characteristic of stimulus with a numerical quantification. We allow monkeys to interact with individuals of different social status, while we monitor the viewer monkey's behavior by tracking its scan paths. With these observations, we can understand the learning status of this animal via looking behavior analysis on the stimulus. First, the viewer monkey shows different looking patterns among six different classes. Therefore, we can generate different data descriptors of these classes and observe the classification performance of the machine learning algorithm. Second, we design the ground truth model based on the characteristic of each stimulus. We define the distribution of information from the ratio of the face, body, and background area in the stimulus. Lastly, we link them to figure out whether the viewer monkey learned enough about the information in the stimulus.NIHImmediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]