23 research outputs found
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
Emerging Challenges in Technology-based Support for Surgical Training
This paper stipulates several technological research and development thrusts that can assist in modern day approaches to simulated training of minimally invasive laparoscopic and robot surgery. Basic tenets of such training are explained, and specific areas of research are enumerated. Specifically, augmented and mixed reality are proposed as a means of improving perceptual and clinical decision-making skills, haptics are proposed as mechanism not only to provide force feedback and guidance, but also as a means of reflecting a tactile feel of surgery in simulated training scenarios. Learning optimization is discussed to fine tune the difficulty levels of various exercises. All the above elements can serve as the foundation for building computer-based virtual coaching environments that can reduce the training costs and provide a broader access to learning highly complex, technology driven surgical techniques
Tworzenie programu badawczego na ameryka艅skiej 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 artyku艂 opisuje mo偶liwo艣ci i strategie tworzenia program贸w badawczych z zewn臋trznym finansowaniem na ameryka艅skich uczelniach w dziedzinach 艣cis艂ych (nauki przyrodnicze, technologia, in偶ynieria oraz matematyka). Artyku艂 jest napisany z perspektywy wieloletniego pracownika naukowego, kt贸ry prowadzi badania i przeszed艂 przez wszystkie szczeble kariery naukowej (asystent, profesor nadzwyczajny i profesor zwyczajny) oraz przez kilka lat sta艂 na czele du偶ego wydzia艂u na University of Arizona. Propozycja umowy zatrudnienia dla m艂odszego cz艂onka kadry naukowej powinna zawiera膰 odpowiedni pakiet pocz膮tkowy, kt贸ry umo偶liwia rozpocz臋cie programu badawczego przez otwarcie laboratorium i zatrudnienie laborant贸w spo艣r贸d student贸w. Spektrum 藕r贸de艂 finansowania bada艅 w zakresie nauk 艣cis艂ych jest opisane wraz z kr贸tk膮 wzmiank膮 o obecnym klimacie finansowym i mechanizmach finansowania w USA. Poniewa偶 m艂odszy cz艂onek kadry naukowej zmierzy si臋 niejednokrotnie z odmow膮 przyznania 艣rodk贸w, b臋dzie potrzebowa膰 zach臋ty oraz pragmatycznych porad, kt贸re pomog膮 skupi膰 wysi艂ki, wytrwa膰 i nadal startowa膰 w konkursach dotacyjnych, co ostatecznie zaowocuje uzyskaniem finansowania. Niniejszy artyku艂 zwiera r贸wnie偶 sugestie, jak planowa膰 granty i sk艂ada膰 wnioski. Na zako艅czenie autor wnosi o to, 偶eby kadra naukowa zachowa艂a wysokie standardy akademickiej uczciwo艣ci, etyki i jako艣ci oraz nie ulega艂a pokusie pozyskiwania 艣rodk贸w finansowych jedynie w celu generowania wy偶szych wska藕nik贸w swojej produktywno艣ci
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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]
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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 未 < 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]
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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]