STL: Surprisingly Tricky Logic (for System Validation)

Much of the recent work developing formal methods techniques to specify or learn the behavior of autonomous systems is predicated on a belief that formal specifications are interpretable and useful for humans when checking systems. Though frequently asserted, this assumption is rarely tested. We performed a human experiment (N = 62) with a mix of people who were and were not familiar with formal methods beforehand, asking them to validate whether a set of signal temporal logic (STL) constraints would keep an agent out of harm and allow it to complete a task in a gridworld capture-the-flag setting. Validation accuracy was $45\% \pm 20\%$ (mean $\pm$ standard deviation). The ground-truth validity of a specification, subjects' familiarity with formal methods, and subjects' level of education were found to be significant factors in determining validation correctness. Participants exhibited an affirmation bias, causing significantly increased accuracy on valid specifications, but significantly decreased accuracy on invalid specifications. Additionally, participants, particularly those familiar with formal methods, tended to be overconfident in their answers, and be similarly confident regardless of actual correctness. Our data do not support the belief that formal specifications are inherently human-interpretable to a meaningful degree for system validation. We recommend ergonomic improvements to data presentation and validation training, which should be tested before claims of interpretability make their way back into the formal methods literature

Comparative performance of human and mobile robotic assistants in collaborative fetch-and-deliver tasks

There is an emerging desire across manufacturing industries to deploy robots that support people in their manual work, rather than replace human workers. This paper explores one such opportunity, which is to field a mobile robotic assistant that travels between part carts and the automotive final assembly line, delivering tools and materials to the human workers. We compare the performance of a mobile robotic assistant to that of a human assistant to gain a better understanding of the factors that impact its effectiveness. Statistically significant differences emerge based on type of assistant, human or robot. Interaction times and idle times are statistically significantly higher for the robotic assistant than the human assistant. We report additional differences in participant's subjective response regarding team fluency, situational awareness, comfort and safety. Finally, we discuss how results from the experiment inform the design of a more effective assistant.BMW Grou

Carbon, Metals, and Grain Size Correlate with Bacterial Community Structure in Sediments of a High Arsenic Aquifer

Bacterial communities can exert significant influence on the biogeochemical cycling of arsenic (As). This has globally important implications since As in drinking water affects the health of over 100 million people worldwide, including in the Ganges–Brahmaputra Delta region of Bangladesh where geogenic arsenic in groundwater can reach concentrations of more than 10 times the World Health Organization’s limit. Thus, the goal of this research was to investigate patterns in bacterial community composition across gradients in sediment texture and chemistry in an aquifer with elevated groundwater As concentrations in Araihazar, Bangladesh. We characterized the bacterial community by pyrosequencing 16S rRNA genes from aquifer sediment samples collected at three locations along a groundwater flow path at a range of depths between 1.5 and 15 m. We identified significant differences in bacterial community composition between locations in the aquifer. In addition, we found that bacterial community structure was significantly related to sediment grain size, and sediment carbon (C), manganese (Mn), and iron (Fe) concentrations. Deltaproteobacteria and Chloroflexi were found in higher proportions in silty sediments with higher concentrations of C, Fe, and Mn. By contrast, Alphaproteobacteria and Betaproteobacteria were in higher proportions in sandy sediments with lower concentrations of C and metals. Based on the phylogenetic affiliations of these taxa, these results may indicate a shift to more Fe-, Mn-, and humic substance-reducers in the high C and metal sediments. It is well-documented that C, Mn, and Fe may influence the mobility of groundwater arsenic, and it is intriguing that these constituents may also structure the bacterial community

Haze in Pluto's atmosphere: Results from SOFIA and ground-based observations of the 2015 June 29 Pluto occultation

On UT 29 June 2015, the occultation by Pluto of a bright star (r′ = 11.9) was observed from the Stratospheric Observatory for Infrared Astronomy (SOFIA) and several ground-based stations in New Zealand and Australia. Pre-event astrometry allowed for an in-flight update to the SOFIA team with the result that SOFIA was deep within the central flash zone (~22 km from center). Analysis of the combined data leads to the result that Pluto's middle atmosphere is essentially unchanged from 2011 and 2013 (Person et al. 2013; Bosh et al. 2015); there has been no significant expansion or contraction of the atmosphere. Additionally, our multi-wavelength observations allow us to conclude that a haze component in the atmosphere is required to reproduce the light curves obtained. This haze scenario has implications for understanding the photochemistry of Pluto's atmosphere

Effects of Earth encounters on the physical properties of near-earth objects

Thesis: S.B., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 56-57).The effects of Earth encounters on the physical properties of near-Earth objects (NEOs) have been shown to be significant factors in their evolution. Previous studies have examined the effects of these encounters on reflectance spectra based on observational measurements, and effects such as spin state and shape changes have been studied for specific asteroids and through simulation. In this project, an automated light-curve fitting routine was developed to support data reduction in an ongoing NEO survey. Additionally, data from previous NEO surveys were used to support simulation results by showing differences between encounter and non-encounter populations' rotational frequency distributions. These results demonstrate that Earth encounters have an effect on asteroid rotation by increasing the overall frequency as well as causing a wider distribution of frequencies when compared to non-encounter populations of NEOs. These data were, however, unable to show any effect on asteroid shape brought on by planetary encounters. A frequency comparison between NEOs that likely had Earth encounters to main-belt-equivalent asteroids did not show the same encounter effect, though the 'equivalent' asteroid populations were likely affected by a size/spin-rate bias.by Ho Chit Siu.S.B

Moving and adapting with a learning exoskeleton

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 129-142).The operation of a powered exoskeleton is a type of human-robot interaction with extremely tight human-robot coupling. As exoskeletons become increasingly intelligent, it is increasingly appropriate to think of them not simply as tools, but rather as semi-autonomous teammates. This thesis explores the implementation, operation, and consequences of intelligent exoskeletons - teammates that move and adapt to the human to which they are physically coupled. Exoskeletons have potential applications in several domains, including strength augmentation, injury reduction, and rehabilitation. Appropriately mapping human intent to exoskeleton action is crucial. Generating this mapping can be difficult, as operator movements are constrained by the exoskeletons they are trying to control. This problem is particularly significant with upper-body exoskeletons, where high degrees of freedom allow for much less predictable motion than in the lower body. Surface electromyography (sEMG) - reading electrical signals from muscles - is one way to estimate human intent. sEMG contains anticipatory information that precedes the associated limb movement, allowing for better human-exoskeleton coordination than reactive control methods. However, sEMG is very sensitive to individual physiologies and sensor placement. We use machine learning from demonstration (LfD) to create personalized, robust sEMG mappings for exoskeleton control. We demonstrate classification of transient dynamic grasping gestures with data where sEMG sensors on the forearm have been shifted from a nominal configuration. Next, sEMG-based gesture recognition is applied to exoskeleton control, where sEMG mappings are learned as the exoskeleton is controlled with a pressure-based inputs. Finally, we analyze the human-exoskeleton team performance, fluency, and adaptation using a pressure-based controller, a static sEMG mapping, and a dynamic sEMG mapping. We show that LfD allows us to use anticipatory signaling to reduce human-exoskeleton interaction pressure. Subjects were able to adapt to all three controllers, but team performance and fluency were affected by the controller type and order of exposure. These results have implications for future exoskeleton controller design, and for exoskeleton operator training. They also open up new avenues of research in relation to adaptation to exoskeletons, intent classification algorithms, and the application of metrics from the human-robot interaction literature to the field of human exoskeleton research.by Ho Chit Siu.Ph. D

Implementation of a Surface Electromyography-Based Upper Extremity Exoskeleton Controller Using Learning from Demonstration

Upper-extremity exoskeletons have demonstrated potential as augmentative, assistive, and rehabilitative devices. Typical control of upper-extremity exoskeletons have relied on switches, force/torque sensors, and surface electromyography (sEMG), but these systems are usually reactionary, and/or rely on entirely hand-tuned parameters. sEMG-based systems may be able to provide anticipatory control, since they interface directly with muscle signals, but typically require expert placement of sensors on muscle bodies. We present an implementation of an adaptive sEMG-based exoskeleton controller that learns a mapping between muscle activation and the desired system state during interaction with a user, generating a personalized sEMG feature classifier to allow for anticipatory control. This system is robust to novice placement of sEMG sensors, as well as subdermal muscle shifts. We validate this method with 18 subjects using a thumb exoskeleton to complete a book-placement task. This learning-from-demonstration system for exoskeleton control allows for very short training times, as well as the potential for improvement in intent recognition over time, and adaptation to physiological changes in the user, such as those due to fatigue

A discrete forward-modeling method for characterizing occultation lightcurves of tenuous planetary atmospheres

Thesis: S.M., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2015.Cataloged from PDF version of thesis.Includes bibliographical references (pages 108-110).We present a discrete numerical approach for forward-modeling lightcurves from stellar occultations by planetary atmospheres. Our discrete approach provides a way to arbitrarily set atmospheric properties at any radius from the occulting body, giving it flexibility for applying models of vertical variation in atmospheric conditions. The method is used to examine trends in lightcurve characteristics resulting from changes in the atmosphere of the occulting body. We find that for Pluto-like atmospheres, temperature and pressure variations affect the characteristics of the lightcurve much more than the gas composition. We also find that the half-light radius is more sensitive to atmospheric changes than either the minimum normalized flux or the slope at half-light. Temperature is found to be the most easily-constrained atmospheric parameter, as the gradients for changes in lightcurve characteristics are much more aligned with the temperature axis of the atmospheric parameter space than any other axis. Trends in lightcurve characteristics were examined in and around the parameter space occupied by the atmospheric conditions predicted for Pluto based on the 2011 and 2013 occultation events. Our error analysis method produced uncertainty values consistent with the reported uncertainties for half-light radius. This kind of lightcurve characterization is potentially useful for constraining the level of precision required in measuring given lightcurve characteristics in order to provide certain uncertainty bounds on the atmospheric conditions of the occulting body.by Ho Chit Siu.S.M