Intelligent and High-Performance Behavior Design of Autonomous Systems via Learning, Optimization and Control

Nowadays, great societal demands have rapidly boosted the development of autonomous systems that densely interact with humans in many application domains, from manufacturing to transportation and from workplaces to daily lives. The shift from isolated working environments to human-dominated space requires autonomous systems to be empowered to handle not only environmental uncertainties such as external vibrations but also interaction uncertainties arising from human behavior which is in nature probabilistic, causal but not strictly rational, internally hierarchical and socially compliant.This dissertation is concerned with the design of intelligent and high-performance behavior of such autonomous systems, leveraging the strength from control, optimization, learning, and cognitive science. The work consists of two parts. In Part I, the problem of high-level hybrid human-machine behavior design is addressed. The goal is to achieve safe, efficient and human-like interaction with people. A framework based on the theory of mind, utility theories and imitation learning is proposed to efficiently represent and learn the complicated behavior of humans. Built upon that, machine behaviors at three different levels - the perceptual level, the reasoning level, and the action level - are designed via imitation learning, optimization, and online adaptation, allowing the system to interpret, reason and behave as human, particularly when a variety of uncertainties exist. Applications to autonomous driving are considered throughout Part I. Part II is concerned with the design of high-performance low-level individual machine behavior in the presence of model uncertainties and external disturbances. Advanced control laws based on adaptation, iterative learning and the internal structures of uncertainties/disturbances are developed to assure that the high-level interactive behaviors can be reliably executed. Applications on robot manipulators and high-precision motion systems are discussed in this part

Development of a Water Education Module for Middle School Students under the Guidance of the Chihuahuan Desert Nature Park and based on EPSCoR funded Research on Evapotranspiration along the Middle Rio Grande

In 2004, a study by S.S. Papadopoulos determined that riparian evapotranspiration (ET) along the Middle Rio Grande (MRG) accounts for 37% of the total water budget in this stretch of the river. Transferring important findings such as this to middle school age students presents both a challenge and an opportunity to provide authentic research based information to tomorrows water managers and inspire their curiosity regarding water issues in New Mexico. This Professional Project presents two activities that incorporate selected aspects of the ET research funded by New Mexico\u27s Experimental Program to Stimulate Competitive Research (EPSCoR) along the Middle Rio Grande. The first activity is entitled Plant Transpiration and the second one is Remote Sensing. The two activities were developed as part of the Water Module of the Chihuahuan Desert Nature Park in Las Cruces, New Mexico and have been aligned to meet New Mexico Science Content Standards for 5th through 8th grade. Currently, the activities were tested in Albuquerque classrooms, and will soon be presented in a teacher workshop in Las Cruces. The Plant Transpiration activity transfers the core question of the current ET research of whether non-native plants lose more water due to ET processes than native plants. The Remote Sensing activity presents Landsat 7 images as a valuable tool for studying the environment from a new perspective. A number of researchers and educators from across New Mexico provided valuable input in developing the two activities

onCampus: October 22, 2009

The Ohio State University Faculty Staff Newspape

Program and Abstracts of the Annual Meeting of the Georgia Academy of Science, 2009

The annual meeting of the Georgia Academy of Science took place April 3-4, 2009, at Spelman College, Atlanta, Georgia. Presentations were provided by members of the Academy who represented the following sections: I. Biological Sciences II Chemistry III. Earth & Atmospheric Sciences IV. Physics, Mathematics, Computer Science, Engineering & Technology V. Biomedical Sciences VI. Philosophy & History of Science VII. Science Education VIII. Anthropology

Counter Unmanned Aircraft Systems Technologies and Operations

As the quarter-century mark in the 21st Century nears, new aviation-related equipment has come to the forefront, both to help us and to haunt us. (Coutu, 2020) This is particularly the case with unmanned aerial vehicles (UAVs). These vehicles have grown in popularity and accessible to everyone. Of different shapes and sizes, they are widely available for purchase at relatively low prices. They have moved from the backyard recreation status to important tools for the military, intelligence agencies, and corporate organizations. New practical applications such as military equipment and weaponry are announced on a regular basis – globally. (Coutu, 2020) Every country seems to be announcing steps forward in this bludgeoning field. In our successful 2nd edition of Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets (Nichols, et al., 2019), the authors addressed three factors influencing UAS phenomena. First, unmanned aircraft technology has seen an economic explosion in production, sales, testing, specialized designs, and friendly / hostile usages of deployed UAS / UAVs / Drones. There is a huge global growing market and entrepreneurs know it. Second, hostile use of UAS is on the forefront of DoD defense and offensive planners. They are especially concerned with SWARM behavior. Movies like “Angel has Fallen,” where drones in a SWARM use facial recognition technology to kill USSS agents protecting POTUS, have built the lore of UAS and brought the problem forefront to DHS. Third, UAS technology was exploding. UAS and Counter- UAS developments in navigation, weapons, surveillance, data transfer, fuel cells, stealth, weight distribution, tactics, GPS / GNSS elements, SCADA protections, privacy invasions, terrorist uses, specialized software, and security protocols has exploded. (Nichols, et al., 2019) Our team has followed / tracked joint ventures between military and corporate entities and specialized labs to build UAS countermeasures. As authors, we felt compelled to address at least the edge of some of the new C-UAS developments. It was clear that we would be lucky if we could cover a few of – the more interesting and priority technology updates – all in the UNCLASSIFIED and OPEN sphere. Counter Unmanned Aircraft Systems: Technologies and Operations is the companion textbook to our 2nd edition. The civilian market is interesting and entrepreneurial, but the military and intelligence markets are of concern because the US does NOT lead the pack in C-UAS technologies. China does. China continues to execute its UAS proliferation along the New Silk Road Sea / Land routes (NSRL). It has maintained a 7% growth in military spending each year to support its buildup. (Nichols, et al., 2019) [Chapter 21]. They continue to innovate and have recently improved a solution for UAS flight endurance issues with the development of advanced hydrogen fuel cell. (Nichols, et al., 2019) Reed and Trubetskoy presented a terrifying map of countries in the Middle East with armed drones and their manufacturing origin. Guess who? China. (A.B. Tabriski & Justin, 2018, December) Our C-UAS textbook has as its primary mission to educate and train resources who will enter the UAS / C-UAS field and trust it will act as a call to arms for military and DHS planners.https://newprairiepress.org/ebooks/1031/thumbnail.jp

Mobility in the Advent of Autonomous Driving – Toward an Understanding of User Acceptance and Quality Perception Factors

Recent advancements in intelligent technologies and sensor-based data collections pave the way for autonomous driving and facilitate a radical transformation of today’s mobility. Based on auspicious market projections, traditional automotive manufacturers and technology companies invest heavily in the development of autonomous vehicles (AVs). In addition to the profits that the industry expects from self-driving vehicles, this new type of mobility should also solve societal issues like reducing traffic accidents and fatalities by eliminating human driving errors. More efficient autonomous driving is expected to bring improvements in terms of fewer congestions and less fuel consumption, thereby reducing greenhouse emissions. Besides, AVs pledge to entail advantages for their users. Specifically, they increase mobility for the disabled and the older generation. In contrast, younger passengers associate autonomous driving with improved productivity and an enhanced hedonic experience as non-driving activities, such as working or watching a movie, are made possible. Contrary to the above expectations, people also raise concerns regarding self-driving vehicles. They are worried about whether the sensors and systems can correctly interpret complex environmental conditions. Above all, there are doubts whether the technology, even being intelligent, can react appropriately in critical traffic situations made up of humans who sometimes behave unpredictably. In case of unavoidable traffic accidents, ethical questions come into play regarding how the vehicle makes decisions that could result in a person being injured or killed. Finally, the new and sophisticated technology could have vulnerabilities that can be exploited by cybercriminals or allow unauthorized third parties to obtain passenger data. Motivated by the anticipated improvements that AVs entail and the breadth of factors that might influence their adoption, a large body of research investigating relevant adoption factors has accumulated. In order to collect, organize, and combine extant findings, research paper A conducts a structured literature review on the acceptance of autonomous vehicles. Based on 58 articles, it develops an AV acceptance framework consisting of individual user characteristics, vehicle characteristics, and political/societal elements. The framework indicates for each factor whether available research results identify the effect as either positively or negatively significant. Thereby, the paper also sheds light on diverging construct operationalizations, aiming to support researchers in comparing available findings. Eventually, paper A proposes future research avenues across various themes and methods, which build a foundation for further research pursued in this dissertation’s subsequent papers. However, solely balancing significant against non-significant results can come to wrong conclusions since the sample size alone can lead to varying significance levels. Because of this, paper B builds on the literature review and conducts a meta-analysis to include further quantitative analyses. It calculates the mean effect sizes for each AV acceptance factor based on published research results. By doing so, the paper identifies attitude, perceived usefulness, efficiency, trust in AVs, safety, and subjective norms to correlate most strongly with the behavioral intention to use an automated car. A subsequent moderator-analysis shows that almost all acceptance factors are influenced by the study’s methodology and location, the AV’s level of automation, and the examined ownership model, i.e., private cars, car sharing, or public transport. In doing so, paper B observes that most of the available research is on privately owned AVs and hence lacks to assess public as well as shared automated mobility. To fill this gap, paper C investigates characteristics relevant for automated mobility as a service (AMaaS). Based on 23 exploratory interviews with the general public, the paper derives a set of AMaaS requirements. Mobility experts sort these requirements based on commonalities so that a cluster analysis can conceptualize the expected AMaaS characteristics from a practitioner’s view. The paper identifies traffic safety, information privacy, cybersecurity, regulations, flexibility, accessibility, efficiency, and convenience to be relevant service characteristics. It discusses each required characteristic and thereby delineates the constructs’ scopes so that subsequent research can build appropriate measurement instruments. Besides, paper C discovers strongly diverging priorities regarding the respective service characteristics when comparing the potential users’ conversation shares with the experts’ relevance ratings. Paper D builds on the qualitative results of paper C as it develops and validates a hierarchical quality scale for AMaaS. The paper proposes a theoretical model and operationalizes the previously identified service characteristics. Throughout multiple empirical studies with 1,431 participants, the proposed quality scale is refined iteratively until satisfactory psychometric properties are achieved. Nomological validity ensures the scale’s predictability. Paper D progresses research from focussing on the mere acceptance of autonomous driving to the user’s quality perception, which significantly influences user satisfaction and the success of AMaaS. This, in turn, is necessary to realize the promised benefits of autonomous driving in a sustainable manner

Multi-modal post-editing of machine translation

As MT quality continues to improve, more and more translators switch from traditional translation from scratch to PE of MT output, which has been shown to save time and reduce errors. Instead of mainly generating text, translators are now asked to correct errors within otherwise helpful translation proposals, where repetitive MT errors make the process tiresome, while hard-to-spot errors make PE a cognitively demanding activity. Our contribution is three-fold: first, we explore whether interaction modalities other than mouse and keyboard could well support PE by creating and testing the MMPE translation environment. MMPE allows translators to cross out or hand-write text, drag and drop words for reordering, use spoken commands or hand gestures to manipulate text, or to combine any of these input modalities. Second, our interviews revealed that translators see value in automatically receiving additional translation support when a high CL is detected during PE. We therefore developed a sensor framework using a wide range of physiological and behavioral data to estimate perceived CL and tested it in three studies, showing that multi-modal, eye, heart, and skin measures can be used to make translation environments cognition-aware. Third, we present two multi-encoder Transformer architectures for APE and discuss how these can adapt MT output to a domain and thereby avoid correcting repetitive MT errors.Angesichts der stetig steigenden Qualität maschineller Übersetzungssysteme (MÜ) post-editieren (PE) immer mehr Übersetzer die MÜ-Ausgabe, was im Vergleich zur herkömmlichen Übersetzung Zeit spart und Fehler reduziert. Anstatt primär Text zu generieren, müssen Übersetzer nun Fehler in ansonsten hilfreichen Übersetzungsvorschlägen korrigieren. Dennoch bleibt die Arbeit durch wiederkehrende MÜ-Fehler mühsam und schwer zu erkennende Fehler fordern die Übersetzer kognitiv. Wir tragen auf drei Ebenen zur Verbesserung des PE bei: Erstens untersuchen wir, ob andere Interaktionsmodalitäten als Maus und Tastatur das PE unterstützen können, indem wir die Übersetzungsumgebung MMPE entwickeln und testen. MMPE ermöglicht es, Text handschriftlich, per Sprache oder über Handgesten zu verändern, Wörter per Drag & Drop neu anzuordnen oder all diese Eingabemodalitäten zu kombinieren. Zweitens stellen wir ein Sensor-Framework vor, das eine Vielzahl physiologischer und verhaltensbezogener Messwerte verwendet, um die kognitive Last (KL) abzuschätzen. In drei Studien konnten wir zeigen, dass multimodale Messung von Augen-, Herz- und Hautmerkmalen verwendet werden kann, um Übersetzungsumgebungen an die KL der Übersetzer anzupassen. Drittens stellen wir zwei Multi-Encoder-Transformer-Architekturen für das automatische Post-Editieren (APE) vor und erörtern, wie diese die MÜ-Ausgabe an eine Domäne anpassen und dadurch die Korrektur von sich wiederholenden MÜ-Fehlern vermeiden können.Deutsche Forschungsgemeinschaft (DFG), Projekt MMP