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Human-automated vehicle interactions
This dissertation is proposed to answer the question: how can the interactions between human and automated vehicles be used to improve the overall performance of automated driving technology? Multiple different modules in automated vehicles such as the perception, motion plan and motion control modules can potentially be benefitted from human-automated vehicle interactions. For perception module, the self-correction of faulty sensors can be achieved using human demonstration data. For motion plan and motion control modules, the performance of the low-level motion controller can be improved with the help of human demonstration, and the behavior of the motion planner can be improved using human intervention data during automated driving. Moreover, a better model for a human driver could improve the overall efficiency and comfort of vehicles in connected mixed traffic. In this dissertation, the technical research toward these goals has been completed and has resulted in several peer-reviewed publications. Optimization methods and model predictive control are used extensively to improve energy efficiency while maintaining safe and comfort driving. An inverse model predictive control (IMPC) method has been developed and it has been proven to be effective in modeling the motion of human driven vehicles. The proposed method has demonstrated its benefits in both connected automated highway driving and the bilateral adaptation of human driver and automated driving controller in human-in-the loop simulations. The proposed future research seeks to broaden the application of IMPC by considering a more comprehensive cost function design and applying it to more complex driving situations.
HUMAN-AUTOMATED VEHICLE INTERACTIONS
This dissertation is proposed to answer the question: how can the interactions between human and automated vehicles be used to improve the overall performance of automated driving technology? Multiple different modules in automated vehicles such as the perception, motion plan and motion control modules can potentially be benefitted from human-automated vehicle interactions. For perception module, the self-correction of faulty sensors can be achieved using human demonstration data. For motion plan and motion control modules, the performance of the low-level motion controller can be improved with the help of human demonstration, and the behavior of the motion planner can be improved using human intervention data during automated driving. Moreover, a better model for a human driver could improve the overall efficiency and comfort of vehicles in connected mixed traffic. In this dissertation, the technical research toward these goals has been completed and has resulted in several peer-reviewed publications. Optimization methods and model predictive control are used extensively to improve energy efficiency while maintaining safe and comfort driving. An inverse model predictive control (IMPC) method has been developed and it has been proven to be effective in modeling the motion of human driven vehicles. The proposed method has demonstrated its benefits in both connected automated highway driving and the bilateral adaptation of human driver and automated driving controller in human-in-the loop simulations. The proposed future research seeks to broaden the application of IMPC by considering a more comprehensive cost function design and applying it to more complex driving situations.
A Modified Tactile Brush Algorithm for Complex Touch Gestures
Several researchers have investigated phantom tactile sensation (i.e., the perception of a nonexistent actuator between two real actuators) and apparent tactile motion (i.e., the perception of a moving actuator due to time delays between onsets of multiple actuations). Prior work has focused primarily on determining appropriate Durations of Stimulation (DOS) and Stimulus Onset Asynchronies (SOA) for simple touch gestures, such as a single finger stroke. To expand upon this knowledge, we investigated complex touch gestures involving multiple, simultaneous points of contact, such as a whole hand touching the arm. To implement complex touch gestures, we modified the Tactile Brush algorithm to support rectangular areas of tactile stimulation.
Dynamic modeling of injection-induced fault reactivation and ground motion and impact on surface structures and human perception
We summarize recent modeling studies of injection-induced fault reactivation, seismicity, and its potential impact on surface structures and nuisance to the local human population. We used coupled multiphase fluid flow and geomechanical numerical modeling, dynamic wave propagation modeling, seismology theories, and empirical vibration criteria from mining and construction industries. We first simulated injection-induced fault reactivation, including dynamic fault slip, seismic source, wave propagation, and ground vibrations. From co-seismic average shear displacement and rupture area, we determined the moment magnitude to about M w = 3 for an injection-induced fault reactivation at a depth of about 1000 m. We then analyzed the ground vibration results in terms of peak ground acceleration (PGA), peak ground velocity (PGV), and frequency content, with comparison to the U.S. Bureau of Mines’ vibration criteria for cosmetic damage to buildings, as well as human-perception vibration limits. For the considered synthetic M w = 3 event, our analysis showed that the short duration, high frequency ground motion may not cause any significant damage to surface structures, and would not cause, in this particular case, upward CO 2 leakage, but would certainly be felt by the local population.
Pivotal role of hMT+ in long‐range disambiguation of interhemispheric bistable surface motion
Abstract It remains an open question whether long‐range disambiguation of ambiguous surface motion can be achieved in early visual cortex or instead in higher level regions, which concerns object/surface segmentation/integration mechanisms. We used a bistable moving stimulus that can be perceived as a pattern comprehending both visual hemi‐fields moving coherently downward or as two widely segregated nonoverlapping component objects (in each visual hemi‐field) moving separately inward. This paradigm requires long‐range integration across the vertical meridian leading to interhemispheric binding. Our fMRI study ( n = 30) revealed a close relation between activity in hMT+ and perceptual switches involving interhemispheric segregation/integration of motion signals, crucially under nonlocal conditions where components do not overlap and belong to distinct hemispheres. Higher signal changes were found in hMT+ in response to spatially segregated component (incoherent) percepts than to pattern (coherent) percepts. This did not occur in early visual cortex, unlike apparent motion, which does not entail surface segmentation. We also identified a role for top–down mechanisms in state transitions. Deconvolution analysis of switch‐related changes revealed prefrontal, insula, and cingulate areas, with the right superior parietal lobule (SPL) being particularly involved. We observed that directed influences could emerge either from left or right hMT+ during bistable motion integration/segregation. SPL also exhibited significant directed functional connectivity with hMT+, during perceptual state maintenance (Granger causality analysis). Our results suggest that long‐range interhemispheric binding of ambiguous motion representations mainly reflect bottom–up processes from hMT+ during perceptual state maintenance. In contrast, state transitions maybe influenced by high‐level regions such as the SPL. Hum Brain Mapp 38:4882–4897, 2017 . © 2017 Wiley Periodicals, Inc.
Towards Cooperative Control of Humanoid Robots for Handling High-Consequence Materials in Gloveboxes - 17291
In this paper, we describe our ongoing work with NASA's Valkyrie humanoid robot and present preliminary results on cooperative control of Valkyrie's hands for performing dexterous manipulation tasks inside gloveboxes commonly found in many nuclear facilities. First, we discuss our human-supervised robot control framework which is based on optimization-based whole-body motion and manipulation controllers. A key aspect of this approach is perception based grasping. We develop a grasping control module for realizing the grasps corresponding to sample tasks such as power, ball, key, pinch, and open palm grasps and their variations. Next, we introduce the notion of motion template library in order to develop generalizable robot grasping and manipulation. Motion template library stores the constraint setting information for the constrained motion planning methods and a framework which can implement the motion template library on different types of robots for accomplishing similar tasks. Motion templates are defined only based on the task requirements. As a result, they can be easily ported to different robot platforms. Lastly, we discuss our multi-modal interfaces designs which include a visual display for improved situational awareness as well as a tactile glove for robot hand control and feedback. Our goal is for the person tele-operating the Valkyrie robot to have better sensing and control than what he or she would have if actually standing at the glovebox doing the work. This improved sensing is comprised of the ability to 'see through' the robot's arms and hands in the gloves and to have an improved sense of touch. The paper concludes with a discussion of our validation strategy. Our success metrics are derived from the completion of a relatively complex experiment to be performed in the glovebox. We evaluate various realistic experiments and use them for task validation and demonstration with Valkyrie. We use speed, time of completion, accuracy, repeatability and reliability rates as success metrics by designing replicable experiments. (authors)
Dynamic crystallography reveals early signalling events in ultraviolet photoreceptor UVR8
Abstract not provided
Photoactivation mechanism of a carotenoid-based photoreceptor
Photoprotection is essential for efficient photosynthesis. Cyanobacteria have evolved a unique photoprotective mechanism mediated by a water-soluble carotenoid-based photoreceptor known as orange carotenoid protein (OCP). OCP undergoes large conformational changes in response to intense blue light, and the photoactivated OCP facilitates dissipation of excess energy via direct interaction with allophycocyanins at the phycobilisome core. However, the structural events leading up to the OCP photoactivation remain elusive at the molecular level. Here we present direct observations of light-induced structural changes in OCP captured by dynamic crystallography. Difference electron densities between the dark and illuminated states reveal widespread and concerted atomic motions that lead to altered protein–pigment interactions, displacement of secondary structures, and domain separation. Based on these crystallographic observations together with site-directed mutagenesis, we propose a molecular mechanism for OCP light perception, in which the photochemical property of a conjugated carbonyl group is exploited. We hypothesize that the OCP photoactivation starts with keto–enol tautomerization of the essential 4-keto group in the carotenoid, which disrupts the strong hydrogen bonds between the bent chromophore and the protein moiety. Subsequent structural changes trapped in the crystal lattice offer a high-resolution glimpse of the initial molecular events as OCP begins to transition from the orange-absorbing state to the active red-absorbing state.
Structure Perception in 3D Point Clouds
Understanding human perception is critical to the design of effective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the literature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projections of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rotation, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under rotation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns perceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.
Pattern ANalytics To Support High-performance Exploitation and Reasoning (PANTHER)
Sandia researchers are developing analytic techniques that efficiently detect patterns in high-volume, noisy, remote sensing and other geospatial data, improving an analysts’ ability to detect possibly off-normal events in complex homeland security, nuclear weapons, and emerging threat environments. High-consequence, national security decisions rely on timely, comprehensive answers to complex questions, yet critical gaps in our approach to these questions remain. PANTHER addresses these gaps through fundamental research on: geospatial-temporal feature extraction via image segmentation and classification; geospatial-temporal graph algorithms and computational geometry; and domain-relevant models of human perception and cognition informing the design of analytic systems. PANTHER’s cross-disciplinary R&D approach uses fundamental science and mathematics to understand how to maximize decision systems through rethinking key aspects of geospatial data analysis. New methods in motion and trajectory analysis support both rapid search for known trajectories as well as rapid clustering and anomaly detection. Thus, the perceptual and visual load on users is reduced by providing pattern analytics with elegant visual cues to spatial and temporal characteristics.
Operation Teapot
As part of Operation Teapot, reporter Joan Collin came to the Nevada Test Site in early May 1955 to narrate a Federal Civil Defense Administration motion picture film on the explosive and radioactive effects of a nuclear detonation on food supplies, houses, communication systems, and energy sources. After watching efforts to feed the many people involved in test site activities, Collin asked the question of how to mass feed people after a nuclear attack. She was one of the few persons perceptive enough to recognize the significance of this issue.
Q-VR: System-Level Design for Future Mobile Collaborative Virtual Reality
High Quality Mobile Virtual Reality (VR) is what the incoming graphics technology era demands: users around the world, regardless of their hardware and network conditions, can all enjoy the immersive virtual experience. However, the state-of-the-art software-based mobile VR designs cannot fully satisfy the realtime performance requirements due to the highly interactive nature of user's actions and complex environmental constraints during VR execution. Inspired by the unique human visual system effects and the strong correlation between VR motion features and realtime hardware-level information, we propose Q-VR, a novel dynamic collaborative rendering solution via software-hardware co-design for enabling future low-latency high-quality mobile VR. At software-level, Q-VR provides flexible high-level tuning interface to reduce network latency while maintaining user perception. At hardware-level, Q-VR accommodates a wide spectrum of hardware and network conditions across users by effectively leveraging the computing capability of the increasingly powerful VR hardware. Extensive evaluation on real-world games demonstrates that Q-VR can achieve an average end-to-end performance speedup of 3.4x (up to 6.7x) over the traditional local rendering design in commercial VR devices, and a 4.1x frame rate improvement over the state-of-the-art static collaborative rendering.
Structure Perception in 3D Point Clouds: Preprint
Understanding human perception is critical to the design of ef- fective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the liter- ature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projec- tions of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rota- tion, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under ro- tation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns per- ceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.
Exploring the effectiveness of a back-supporting exosuit: Trunk muscle activity and user experience in controlled and real-world shoveling scenarios
Introduction: This study evaluates the effectiveness of a passive wearable exosuit (HeroWear Apex) in reducing lumbar muscle effort while shoveling. Method: Two experiments were conducted, involving: (1) moving calibrated sandbags at a predefined pace in a laboratory, and (2) moving loose dirt in an in-field setting. Studies were designed to emulate real-world shoveling conditions at Department of Energy - Environmental Management sites. Muscle activity of the lumbar and oblique muscles was analyzed, along with user perceptions. Due to the asymmetric nature of shoveling, analysis of muscle activity was split between the weighted and unweighted sides, with the weighted side being defined as the side of the body closest to the head of the shovel in a neutral posture. Results: While donning the device, both experiments showed a significant decrease in muscle activity for at least one lumbar muscle on the weighted side. Participants rated the device with a high usability score, and perceived exertion ratings were significantly lower while wearing the exosuit. While opinions varied regarding the device’s helpfulness, participants felt the device was comfortable and did not hinder motion during the task. Practical applications: The reduction in back muscle activity associated with wearing the exosuit has the potential to reduce muscle fatigue resulting from repetitive motions.
Transience of the Retinal Output Is Determined by a Great Variety of Circuit Elements
Retinal ganglion cells (RGCs) encrypt stimulus features of the visual scene in action potentials and convey them toward higher visual centers in the brain. Although there are many visual features to encode, our recent understanding is that the ~46 different functional subtypes of RGCs in the retina share this task. In this scheme, each RGC subtype establishes a separate, parallel signaling route for a specific visual feature (e.g., contrast, the direction of motion, luminosity), through which information is conveyed. The efficiency of encoding depends on several factors, including signal strength, adaptational levels, and the actual efficacy of the underlying retinal microcircuits. Upon collecting inputs across their respective receptive field, RGCs perform further analysis (e.g., summation, subtraction, weighting) before they generate the final output spike train, which itself is characterized by multiple different features, such as the number of spikes, the inter-spike intervals, response delay, and the rundown time (transience) of the response. These specific kinetic features are essential for target postsynaptic neurons in the brain in order to effectively decode and interpret signals, thereby forming visual perception. We review recent knowledge regarding circuit elements of the mammalian retina that participate in shaping RGC response transience for optimal visual signaling.