15,322 results on '"Tomlin AS"'
Search Results
102. A Brief History of Children’s Rights
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Sacotte, Kaitlyn, Tomlin, Brandon, Judkins, Allison, Brunelli, Luca, Sacotte, Kaitlyn, Tomlin, Brandon, Judkins, Allison, Brunelli, Luca, Persson, Stephanie, With Contrib. by, and Giovanelli, Meredith, With Contrib. by
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- 2023
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103. Impedance response of ionic liquids in long slit pores
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Tomlin, Ruben J., Roy, Tribeni, Kirk, Toby L., Marinescu, Monica, and Gillespie, Dirk
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Condensed Matter - Soft Condensed Matter ,Condensed Matter - Mesoscale and Nanoscale Physics - Abstract
We study the dynamics of ionic liquids in a thin slit pore geometry. Beginning with the classical and dynamic density functional theories for systems of charged hard spheres, an asymptotic procedure leads to a simplified model which incorporates both the accurate resolution of the ion layering (perpendicular to the slit pore wall) and the ion transport in the pore length. This reduced-order model enables qualitative comparisons between different ionic liquids and electrode pore sizes at low numerical expense. We derive semi-analytical expressions for the impedance response of the reduced-order model involving numerically computable sensitivities, and obtain effective finite-space Warburg elements valid in the high and low frequency limits. Additionally, we perform time-dependent numerical simulations to recover the impedance response as a cross-validation step. We investigate the dependence of the impedance response on system parameters and the choice of density functional theory used. The inclusion of electrostatic effects beyond mean-field qualitatively changes the dependence of the characteristic response time on the pore width. We observe peaks in the response time as a function of pore width, with height and location depending on the potential difference imposed. We discuss how the calculated dynamic properties can be used together with equilibrium results to optimise ionic liquid supercapacitors for a given application.
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- 2021
104. Incorporating Data Uncertainty in Object Tracking Algorithms
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Muthali, Anish, Laine, Forrest, and Tomlin, Claire
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Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Methodologies for incorporating the uncertainties characteristic of data-driven object detectors into object tracking algorithms are explored. Object tracking methods rely on measurement error models, typically in the form of measurement noise, false positive rates, and missed detection rates. Each of these quantities, in general, can be dependent on object or measurement location. However, for detections generated from neural-network processed camera inputs, these measurement error statistics are not sufficient to represent the primary source of errors, namely a dissimilarity between run-time sensor input and the training data upon which the detector was trained. To this end, we investigate incorporating data uncertainty into object tracking methods such as to improve the ability to track objects, and particularly those which out-of-distribution w.r.t. training data. The proposed methodologies are validated on an object tracking benchmark as well on experiments with a real autonomous aircraft., Comment: For associated video, see https://youtu.be/S21EvaAynRg
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- 2021
105. Towards cyber-physical systems robust to communication delays: A differential game approach
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Deka, Shankar A., Lee, Donggun, and Tomlin, Claire J.
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Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Robotics ,Mathematics - Dynamical Systems ,34K35, 49L12, 93D21 - Abstract
Collaboration between interconnected cyber-physical systems is becoming increasingly pervasive. Time-delays in communication channels between such systems are known to induce catastrophic failure modes, like high frequency oscillations in robotic manipulators in bilateral teleoperation or string instability in platoons of autonomous vehicles. This paper considers nonlinear time-delay systems representing coupled robotic agents, and proposes controllers that are robust to time-varying communication delays. We introduce approximations that allow the delays to be considered as implicit control inputs themselves, and formulate the problem as a zero-sum differential game between the stabilizing controllers and the delays acting adversarially. The ensuing optimal control law is finally compared to known results from Lyapunov-Krasovskii based approaches via numerical experiments., Comment: 7 pages, 5 figures, Submitted to IEEE Control Systems Letters
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- 2021
106. Multi-Task Learning with Sequence-Conditioned Transporter Networks
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Lim, Michael H., Zeng, Andy, Ichter, Brian, Bandari, Maryam, Coumans, Erwin, Tomlin, Claire, Schaal, Stefan, and Faust, Aleksandra
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Robotics ,Electrical Engineering and Systems Science - Systems and Control - Abstract
Enabling robots to solve multiple manipulation tasks has a wide range of industrial applications. While learning-based approaches enjoy flexibility and generalizability, scaling these approaches to solve such compositional tasks remains a challenge. In this work, we aim to solve multi-task learning through the lens of sequence-conditioning and weighted sampling. First, we propose a new suite of benchmark specifically aimed at compositional tasks, MultiRavens, which allows defining custom task combinations through task modules that are inspired by industrial tasks and exemplify the difficulties in vision-based learning and planning methods. Second, we propose a vision-based end-to-end system architecture, Sequence-Conditioned Transporter Networks, which augments Goal-Conditioned Transporter Networks with sequence-conditioning and weighted sampling and can efficiently learn to solve multi-task long horizon problems. Our analysis suggests that not only the new framework significantly improves pick-and-place performance on novel 10 multi-task benchmark problems, but also the multi-task learning with weighted sampling can vastly improve learning and agent performances on individual tasks.
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- 2021
107. Discretizing Dynamics for Maximum Likelihood Constraint Inference
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Stocking, Kaylene C., McPherson, David L., Matthew, Robert P., and Tomlin, Claire J.
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Computer Science - Robotics ,Electrical Engineering and Systems Science - Systems and Control - Abstract
Maximum likelihood constraint inference is a powerful technique for identifying unmodeled constraints that affect the behavior of a demonstrator acting under a known objective function. However, it was originally formulated only for discrete state-action spaces. Continuous dynamics are more useful for modeling many real-world systems of interest, including the movements of humans and robots. We present a method to generate a tabular state-action space that approximates continuous dynamics and can be used for constraint inference on demonstrations that obey the true system dynamics. We then demonstrate accurate constraint inference on nonlinear pendulum systems with 2- and 4-dimensional state spaces, and show that performance is robust to a range of hyperparameters. The demonstrations are not required to be fully optimal with respect to the objective, and the most likely constraints can be identified even when demonstrations cover only a small portion of the state space. For these reasons, the proposed approach may be especially useful for inferring constraints on human demonstrators, which has important applications in human-robot interaction and biomechanical medicine., Comment: 10 pages, 7 figures
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- 2021
108. Lax Formulae for Efficiently Solving Two Classes of State-Constrained Optimal Control Problems
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Lee, Donggun and Tomlin, Claire J.
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Mathematics - Optimization and Control ,Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper presents Lax formulae for solving the following optimal control problems: minimize the maximum (or the minimum) cost over a time horizon, while satisfying a state constraint. We present a viscosity theory, and by applying the theory to the Hamilton-Jacobi (HJ) equations, these Lax formulae are derived. A numerical algorithm for the Lax formulae is presented: under certain conditions, this algorithm's computational complexity is polynomial in the dimension of the state. For each class of optimal control problem, an example demonstrates the use and performance of the Lax formulae.
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- 2021
109. Two-Year Optical Site Characterization for the Pacific Ocean Neutrino Experiment P-ONE in the Cascadia Basin
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Bailly, Nicolai, Bedard, Jeannette, Böhmer, Michael, Bosma, Jeff, Brussow, Dirk, Cheng, Jonathan, Clark, Ken, Croteau, Beckey, Danninger, Matthias, De Leo, Fabio, Deis, Nathan, Ens, Matthew, Fox, Rowan, Fruck, Christian, Gärtner, Andreas, Gernhäuser, Roman, Ghuman, Dilraj, Grant, Darren, He, Helen, Henningsen, Felix, Holzapfel, Kilian, Hotte, Ryan, Jenkyns, Reyna, Johnson, Hamish, Katil, Akanksha, Kopper, Claudio, Krauss, Carsten B., Kulin, Ian, Leismüller, Klaus, Leys, Sally, Lin, Tony, Macoun, Paul, Man, Matthew, McElroy, Thomas, Meighen-Berger, Stephan, Michel, Jan, Moore, Roger, Morley, Mike, Papp, Laszlo, Pirenne, Benoit, Qiu, Tom, Rankin, Mark, Rea, Immacolata Carmen, Resconi, Elisa, Round, Adrian, Ruskey, Albert, Rutley, Ryan, Spannfellner, Christian, Stacho, Jakub, Timmerman, Ross, Tomlin, Meghan, Tradewell, Matt, Traxler, Michael, Uganecz, Matt, Wagner, Seann, Yañez, Juan Pablo, and Zheng, Yinsong
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Astrophysics - Instrumentation and Methods for Astrophysics ,High Energy Physics - Experiment - Abstract
The STRings for Absorption length in Water (STRAW) are the first in a series of pathfinders for the Pacific Ocean Neutrino Experiment (P-ONE), a future large-scale neutrino telescope in the north-eastern Pacific Ocean. STRAW consists of two 150 m long mooring lines instrumented with optical emitters and detectors. The pathfinder is designed to measure the attenuation length of the water and perform a long-term assessment of the optical background at the future P-ONE site. After two years of continuous operation, measurements from STRAW show an optical attenuation length of about 28 metres at 450 nm. Additionally, the data allow a study of the ambient undersea background. The overall optical environment reported here is comparable to other deep-water neutrino telescopes and qualifies the site for the deployment of P-ONE., Comment: 11 pages, 13 figures
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- 2021
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110. Supporting Emergency Medical Services Clinicians Through Acute and Sustained Crises With Informal Peer Support and Intentional Acts of Kindness: The Emergency Medical Services Code Lavender Program
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Maloney, Lauren M., Hoffman, Jason, Peralta, Edder, Princi, Rudolph, Thode, Henry C., Jr, Tomlin, Mark, DiDonato, Christopher, LaBarbera, Anthony, Lambert, Erin, King, James, Johnson, Daniel G., Edouard, Shawn, and Williams, Sarah
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- 2024
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111. Safe and efficient practice of parenteral nutrition in neonates and children aged 0–18 years – The role of licensed multi-chamber bags
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Senterre, Thibault, van den Akker, Chris H.P., Domellof, Magnus, Saenz de Pipaon, Miguel, Arnell, Henrik, Tabbers, Merit, Valla, Frederic V., Tomlin, Stephen, Paulsson, Mattias, Wackernagel, Dirk, Haiden, Nadja, Luukkainen, Päivi, Orfeo, Luigi, Carnielli, Virgilio P., and Rigo, Jacques
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- 2024
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112. Lithium-ion battery model parametrisation: BatPar an all-in-one toolkit for equivalent circuit models
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Zhu, Tao, Tomlin, Ruben, Garcia, Carlos, Rawat, Sunil, Holland, Thomas, Offer, Gregory, and Marinescu, Monica
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- 2024
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113. Methodology to establish a forming process window for thermoset aligned discontinuous fiber composites
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Tomlin, Loren J., Cender, Thomas A., Sauerbrunn, Steven, and Advani, Suresh G.
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- 2024
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114. Implementation and evaluation of participatory advisory boards in mental health research: a research protocol of the ‘PART-Beirat’ project
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Ferra, Fenia, Drewelow, Eva, Klein, Olga, Daum, Marcel, Walde, Peggy, Gerullis, Kai, Kilimann, Ingo, Tomlin, Jack, Teipel, Stefan, and Völlm, Birgit
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- 2023
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115. The effect of classroom environment on literacy development
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Rance, Gary, Dowell, Richard C., and Tomlin, Dani
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- 2023
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116. Critical care pharmacy workforce: a 2020 re-evaluation of the UK deployment and characteristics
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Borthwick, Mark, Barton, Greg, Ioannides, Christopher P., Forrest, Ruth, Graham-Clarke, Emma, Hanks, Fraser, James, Christie, Kean, David, Sapsford, David, Timmins, Alan, Tomlin, Mark, Warburton, John, and Bourne, Richard S.
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- 2023
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117. Preclinical validation of NeoWarm, a low-cost infant warmer and carrier device, to ameliorate induced hypothermia in newborn piglets as models for human neonates
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Nick D. P. Bluhm, Grant M. Tomlin, Orlando S. Hoilett, Elena A. Lehner, Benjamin D. Walters, Alyson S. Pickering, Kevin Alessandro Bautista, Sherri L. Bucher, and Jacqueline C. Linnes
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low to middle income country (LMIC) ,neonatal hypothermia ,thermal model ,piglet model ,kangaroo mother care (KMC) ,vital signs monitoring system (VSMS) ,Pediatrics ,RJ1-570 - Abstract
IntroductionApproximately 1.5 million neonatal deaths occur among premature and small (low birthweight or small-for gestational age) neonates annually, with a disproportionate amount of this mortality occurring in low- and middle-income countries (LMICs). Hypothermia, the inability of newborns to regulate their body temperature, is common among prematurely born and small babies, and often underlies high rates of mortality in this population. In high-resource settings, incubators and radiant warmers are the gold standard for hypothermia, but this equipment is often scarce in LMICs. Kangaroo Mother Care/Skin-to-skin care (KMC/STS) is an evidence-based intervention that has been targeted for scale-up among premature and small neonates. However, KMC/STS requires hours of daily contact between a neonate and an able adult caregiver, leaving little time for the caregiver to care for themselves. To address this, we created a novel self-warming biomedical device, NeoWarm, to augment KMC/STS. The present study aimed to validate the safety and efficacy of NeoWarm.MethodsSixteen, 0-to-5-day-old piglets were used as an animal model due to similarities in their thermoregulatory capabilities, circulatory systems, and approximate skin composition to human neonates. The piglets were placed in an engineered cooling box to drop their core temperature below 36.5°C, the World Health Organizations definition of hypothermia for human neonates. The piglets were then warmed in NeoWarm (n = 6) or placed in the ambient 17.8°C ± 0.6°C lab environment (n = 5) as a control to assess the efficacy of NeoWarm in regulating their core body temperature.ResultsAll 6 piglets placed in NeoWarm recovered from hypothermia, while none of the 5 piglets in the ambient environment recovered. The piglets warmed in NeoWarm reached a significantly higher core body temperature (39.2°C ± 0.4°C, n = 6) than the piglets that were warmed in the ambient environment (37.9°C ± 0.4°C, n = 5) (p
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- 2024
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118. In vitro biological control of Pyrrhoderma noxium using volatile compounds produced by termite gut-associated streptomycetes
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Cherrihan Adra, Harrchun Panchalingam, Keith Foster, Russell Tomlin, R. Andrew Hayes, and D. İpek Kurtböke
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Streptomyces ,streptomycetes ,termites ,termite gut symbiosis ,antifungal compounds ,volatile organic compounds ,Plant culture ,SB1-1110 - Abstract
IntroductionPyrrhoderma noxium is a plant pathogen that causes economic losses in agricultural and forestry industries, including significant destruction to amenity trees within the city of Brisbane in Australia. Use of chemical control agents are restricted in public areas, there is therefore an urgent need to investigate biological control approaches. Members of the phylum Actinomycetota, commonly known as actinomycetes, are known for their industrially important secondary metabolites including antifungal agents. They have proven to be ideal candidates to produce environmentally friendly compounds including the volatile organic compounds (VOCs) which can be used as biofumigants.MethodsDifferent Streptomyces species (n=15) previously isolated from the guts of termites and stored in the University of the Sunshine Coast’sMicrobial Library were tested for their antifungal VOCs against Pyrrhoderma noxium.ResultsFourteen of them were found to display inhibition (39.39-100%) to the mycelial development of the pathogen. Strongest antifungal activity displaying isolates USC-592, USC-595, USC-6910 and USC-6928 against the pathogen were selected for further investigations. Their VOCs were also found to have plant growth promotional activity observed for Arabidopsis thaliana with an increase of root length (22-36%) and shoot length (26-57%). The chlorophyll content of the test plant had a slight increase of 11.8% as well. Identified VOCs included geosmin, 2-methylisoborneol, 2-methylbutyrate, methylene cyclopentane, β-pinene, dimethyl disulfide, ethyl isovalerate, methoxyphenyl-oxime and α-pinene. Additionally, all 15 Streptomyces isolates were found to produce siderophores and indole acetic acid as well as the enzyme chitinase which is known to break down the fungal cell wall.DiscussionFindings indicate that termite gut-associated streptomycetes might be used to control Pyrrhoderma noxium by utilizing their wide range of inhibitory mechanisms.
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- 2024
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119. Mandatory substance use treatment for justice-involved persons in Germany: a systematic review of reoffending, treatment and the recurrence of substance use outcomes
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Jack Tomlin, Esther Meise, Juliane Wegner, and Birgit Völlm
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forensic mental health ,substance use disorder ,mandatory treatment ,Germany ,reoffending ,Psychiatry ,RC435-571 - Abstract
Many jurisdictions implement mandatory substance use treatment for justice-involved persons. Germany is one such country; however, debates about the appropriateness and effectiveness of this disposal abound. Very little attention has been paid in the international literature to patients receiving mandatory treatment in Germany. This systematic review synthesises research on patients receiving substance use treatment in forensic hospitals under §64 of the German Penal Code with regard to three primary outcomes: treatment completion, reoffending, and the recurrence of substance use. Forty-five publications reporting on 36 studies were reviewed; publication dates ranged from 1988 to 2023. On average, 47% of patients did not successfully complete treatment, compared to 45% who did. Average follow-up reconviction rates were higher than in mentally ill and general offender populations as reported elsewhere. Approximately half of all patients reused substances during treatment. Suggestions for future research, including a focus on strength- and recovery-based indicators, and harmonising routine outcomes measurements, are given.
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- 2024
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120. Micro-spectroscopic and freezing characterization of ice-nucleating particles collected in the marine boundary layer in the eastern North Atlantic
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Knopf, Daniel A, Charnawskas, Joseph C, Wang, Peiwen, Wong, Benny, Tomlin, Jay M, Jankowski, Kevin A, Fraund, Matthew, Veghte, Daniel P, China, Swarup, Laskin, Alexander, Moffet, Ryan C, Gilles, Mary K, Aller, Josephine Y, Marcus, Matthew A, Raveh-Rubin, Shira, and Wang, Jian
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Climate Action ,Astronomical and Space Sciences ,Atmospheric Sciences ,Meteorology & Atmospheric Sciences - Abstract
Formation of atmospheric ice plays a crucial role in the microphysical evolution of mixed-phase and cirrus clouds and thus climate. How aerosol particles impact ice crystal formation by acting as ice-nucleating particles (INPs) is a subject of intense research activities. To improve understanding of atmospheric INPs, we examined daytime and nighttime particles collected during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign conducted in summer 2017. Collected particles, representative of a remote marine environment, were investigated for their propensity to serve as INPs in the immersion freezing (IMF) and deposition ice nucleation (DIN) modes. The particle population was characterized by chemical imaging techniques such as computer-controlled scanning electron microscopy with energy-dispersive X-ray analysis (CCSEM/EDX) and scanning transmission X-ray microscopy with near-edge X-ray absorption fine-structure spectroscopy (STXM/NEXAFS). Four major particle-type classes were identified where internally mixed inorganic-organic particles make up the majority of the analyzed particles. Following ice nucleation experiments, individual INPs were identified and characterized by SEM/EDX. The identified INP types belong to the major particle-type classes consisting of fresh sea salt with organics or processed sea salt containing dust and sulfur with organics. Ice nucleation experiments show IMF events at temperatures as low as 231 K, including the subsaturated regime. DIN events were observed at lower temperatures of 210 to 231 K. IMF and DIN observations were analyzed with regard to activated INP fraction, ice-nucleation active site (INAS) densities, and a water activity-based immersion freezing model (ABIFM) yielding heterogeneous ice nucleation rate coefficients. Observed IMF and DIN events of ice formation and corresponding derived freezing rates demonstrate that the marine boundary layer aerosol particles can serve as INPs under typical mixed-phase and cirrus cloud conditions. The derived IMF and DIN parameterizations allow for implementation in cloud and climate models to evaluate predictive effects of atmospheric ice crystal formation.
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- 2022
121. Hamilton-Jacobi Equations for Two Classes of State-Constrained Zero-Sum Games
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Lee, Donggun and Tomlin, Claire J.
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Mathematics - Optimization and Control ,Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper presents Hamilton-Jacobi (HJ) formulations for two classes of two-player zero-sum games: one with a maximum cost value over time, and one with a minimum cost value over time. In the zero-sum game setting, player A minimizes the given cost while satisfying state constraints, and player B wants to prevent player A's success. For each class of problems, this paper presents two HJ equations: one for time-varying dynamics, cost, and state constraint; the other for time-invariant dynamics, cost, and state constraint. Utilizing the HJ equations, the optimal control for each player is analyzed, and a numerical algorithm is presented to compute the solution to the HJ equations. A two-dimensional water system is introduced as an example to demonstrate the proposed HJ framework.
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- 2021
122. A Computationally Efficient Hamilton-Jacobi-based Formula for State-Constrained Optimal Control Problems
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Lee, Donggun and Tomlin, Claire J.
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Electrical Engineering and Systems Science - Systems and Control ,Mathematics - Optimization and Control - Abstract
This paper investigates a Hamilton-Jacobi (HJ) analysis to solve finite-horizon optimal control problems for high-dimensional systems. Although grid-based methods, such as the level-set method [1], numerically solve a general class of HJ partial differential equations, the computational complexity is exponential in the dimension of the continuous state. To manage this computational complexity, methods based on Lax-Hopf theory have been developed for the state-unconstrained optimal control problem under certain assumptions, such as affine dynamics and state-independent stage cost. Based on the Lax formula [2], this paper proposes an HJ formula for the state-constrained optimal control problem for nonlinear systems. We call this formula \textit{the generalized Lax formula} for the optimal control problem. The HJ formula provides both the optimal cost and an optimal control signal. We also provide an efficient computational method for a class of problems for which the dynamics is affine in the state, and for which the stage and terminal cost, as well as the state constraints, are convex in the state. This class of problems does not require affine dynamics and convex stage cost in the control. This paper also provides three practical examples.
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- 2021
123. Pointwise Feasibility of Gaussian Process-based Safety-Critical Control under Model Uncertainty
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Castañeda, Fernando, Choi, Jason J., Zhang, Bike, Tomlin, Claire J., and Sreenath, Koushil
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Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Machine Learning ,Mathematics - Optimization and Control - Abstract
Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) are popular tools for enforcing safety and stability of a controlled system, respectively. They are commonly utilized to build constraints that can be incorporated in a min-norm quadratic program (CBF-CLF-QP) which solves for a safety-critical control input. However, since these constraints rely on a model of the system, when this model is inaccurate the guarantees of safety and stability can be easily lost. In this paper, we present a Gaussian Process (GP)-based approach to tackle the problem of model uncertainty in safety-critical controllers that use CBFs and CLFs. The considered model uncertainty is affected by both state and control input. We derive probabilistic bounds on the effects that such model uncertainty has on the dynamics of the CBF and CLF. We then use these bounds to build safety and stability chance constraints that can be incorporated in a min-norm convex optimization-based controller, called GP-CBF-CLF-SOCP. As the main theoretical result of the paper, we present necessary and sufficient conditions for pointwise feasibility of the proposed optimization problem. We believe that these conditions could serve as a starting point towards understanding what are the minimal requirements on the distribution of data collected from the real system in order to guarantee safety. Finally, we validate the proposed framework with numerical simulations of an adaptive cruise controller for an automotive system., Comment: The first two authors contributed equally. Accepted for publication in IEEE 60th Conference on Decision and Control (CDC 2021)
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- 2021
124. Inferring Objectives in Continuous Dynamic Games from Noise-Corrupted Partial State Observations
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Peters, Lasse, Fridovich-Keil, David, Rubies-Royo, Vicenç, Tomlin, Claire J., and Stachniss, Cyrill
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Computer Science - Robotics ,Computer Science - Multiagent Systems - Abstract
Robots and autonomous systems must interact with one another and their environment to provide high-quality services to their users. Dynamic game theory provides an expressive theoretical framework for modeling scenarios involving multiple agents with differing objectives interacting over time. A core challenge when formulating a dynamic game is designing objectives for each agent that capture desired behavior. In this paper, we propose a method for inferring parametric objective models of multiple agents based on observed interactions. Our inverse game solver jointly optimizes player objectives and continuous-state estimates by coupling them through Nash equilibrium constraints. Hence, our method is able to directly maximize the observation likelihood rather than other non-probabilistic surrogate criteria. Our method does not require full observations of game states or player strategies to identify player objectives. Instead, it robustly recovers this information from noisy, partial state observations. As a byproduct of estimating player objectives, our method computes a Nash equilibrium trajectory corresponding to those objectives. Thus, it is suitable for downstream trajectory forecasting tasks. We demonstrate our method in several simulated traffic scenarios. Results show that it reliably estimates player objectives from a short sequence of noise-corrupted partial state observations. Furthermore, using the estimated objectives, our method makes accurate predictions of each player's trajectory., Comment: Submitted to RSS2021
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- 2021
125. Physicochemical characterization of free troposphere and marine boundary layer ice-nucleating particles collected by aircraft in the eastern North Atlantic
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D. A. Knopf, P. Wang, B. Wong, J. M. Tomlin, D. P. Veghte, N. N. Lata, S. China, A. Laskin, R. C. Moffet, J. Y. Aller, M. A. Marcus, and J. Wang
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Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
Atmospheric ice nucleation impacts the hydrological cycle and climate by modifying the radiative properties of clouds. To improve our predictive understanding of ice formation, ambient ice-nucleating particles (INPs) need to be collected and characterized. Measurements of INPs at lower latitudes in a remote marine region are scarce. The Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign, in the region of the Azores islands, provided the opportunity to collect particles in the marine boundary layer (MBL) and free troposphere (FT) by aircraft during the campaign's summer and winter intensive operation period. The particle population in samples collected was examined by scanning transmission X-ray microscopy with near-edge X-ray absorption fine structure spectroscopy. The identified INPs were analyzed by scanning electron microscopy with energy-dispersive X-ray analysis. We observed differences in the particle population characteristics in terms of particle diversity, mixing state, and organic volume fraction between seasons, mostly due to dry intrusion events during winter, as well as between the sampling locations of the MBL and FT. These differences are also reflected in the temperature and humidity conditions under which water uptake, immersion freezing (IMF), and deposition ice nucleation (DIN) proceed. Identified INPs reflect typical particle types within the particle population on the samples and include sea salt, sea salt with sulfates, and mineral dust, all associated with organic matter, as well as carbonaceous particles. IMF and DIN kinetics are analyzed with respect to heterogeneous ice nucleation rate coefficients, Jhet, and ice nucleation active site density, ns, as a function of the water criterion Δaw. DIN is also analyzed in terms of contact angles following classical nucleation theory. Derived MBL IMF kinetics agree with previous ACE-ENA ground-site INP measurements. FT particle samples show greater ice nucleation propensity compared to MBL particle samples. This study emphasizes that the types of INPs can vary seasonally and with altitude depending on sampling location, thereby showing different ice nucleation propensities, which is crucial information when representing mixed-phase cloud and cirrus cloud microphysics in models.
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- 2023
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126. Immunomodulatory therapy in children with paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS, MIS-C; RECOVERY): a randomised, controlled, open-label, platform trial
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Faust, Saul N, Haynes, Richard, Jones, Christine E, Staplin, Natalie, Whittaker, Elizabeth, Jaki, Thomas, Juszczak, Ed, Spata, Enti, Wan, Mandy, Bamford, Alasdair, Dimitri, Paul, Finn, Adam, Furness, John, Ramanan, Athimalaipet V, Gale, Christopher, Cathie, Katrina, Drysdale, Simon, Bernatoniene, Jolanta, Murray, Clare, Roehr, Charles C, Fleming, Paul, Riordan, Andrew, Bandi, Srini, Jyothish, Deepthi, Evans, Jennifer, Emonts, Marieke, Kelly, Dominic, Pathan, Nazima, Davies, Patrick, Hague, Rosie, Pollock, Louisa, Semple, Malcolm G, Peto, Leon, Baillie, J Kenneth, Buch, Maya, Jeffery, Katie, Knight, Marian, Lim, Wei Shen, Montgomery, Alan, Mukherjee, Aparna, Mumford, Andrew, Rowan, Kathryn, Thwaites, Guy, Mafham, Marion, Emberson, Jonathan, Landray, Martin J, Horby, Peter W, Chappell, Lucy, Day, Jeremy, Dung, DV, Quang, NN, Binh, Prof, Burhan, E, Alisjahbana, B, Koirala, J, Basnet, S, Kestelyn, E, Basnyat, B, Gyanwali, P, Hamers, RL, Sandercock, P, Darbyshire, J, DeMets, D, Fowler, R, Lalloo, D, Munavvar, M, Roberts, I, Warris, A, Wittes, J, Craddock-Bamford, A, Barton, J, Basoglu, A, Brown, R, Brudlo, W, Denis, E, Fletcher, L, Howard, S, Musini, S, Taylor, K, Cui, G, Goodenough, B, King, A, Lay, M, Murray, D, Stevens, W, Wallendszus, K, Welsh, R, Crichton, C, Davies, J, Goldacre, R, Harper, C, Knight, F, Nunn, M, Salih, H, Welch, J, Campbell, M, Pessoa-Amorim, G, Zayed, M, Wiles, J, Bagley, G, Cameron, S, Chamberlain, S, Farrell, B, Freeman, H, Kennedy, A, Whitehouse, A, Wilkinson, S, Wood, C, Reith, C, Davies, K, Halls, H, Holland, L, Truell, R, Wilson, K, Lingwood, Emma, Howie, L, Lunn, M, Rodgers, Penelope, Amuasi, J, Baird, K, Bao, T, Bittaye, M, Bonney, J, D'Alessandro, U, Dhimal, M, Huyen, T, Jagne, A, Karkey, A, Maiga, O, Matey, E, Nadjm, B, Nel, J, Pant, S, Puspatriani, K, Rahardjani, M, Raijal, S, Rees, H, Rimainar, A, Roberts, C, Rocca, A, Shrestha, S, Usuf, E, Vidaillic, C, Wulandari, F, Alexander, A, Amezaga, M, Armah, C, Asghar, A, Aubrey, P, 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Turner, L, Turner, M, Turner, P, Turner, S, Turner, V, Turner-bone, I, Turney, S, Turvey, J, Tweed, C, Tweed, D, Twemlow, R, Twohey, E, Tyagi, B, Tyagi, V, Tyer, A, Tyler, A, Tyler, J, Tyzack, A, Tzavaras, P, Tzinieris, I, Uddin, A, Uddin, M, Uddin, R, Ugoji, J, Ukaegbu, E, Ul Haq, M, Ul Hassan, W, Ul-Haq, Z, Ullah, S, Um, J, Umaipalan, A, Umate, A, Umeadi, J, Umeh, A, Umeojiako, W, Ummat, B, Underhill, E, Underwood, C, Underwood, J, Uppal, V, Upson, G, Ur Rasool, M, Uriel, A, Urruela, S, Uru, H, Usher, J, Usher, M, Usher-Rea, A, Ustianowski, A, Uzu, H, Vaccari, L, Vaghela, U, Vaidya, A, Vail, D, Valecka, B, Valentine, J, Valeria, B, Vallabhaneni, P, Vallotton, N, Vamplew, L, Vamvakiti, E, Vamvakopoulos, J, van Bruggen, L, van de Venne, M, van der Meer, A, van der Stelt, N, van Koutrik, L, Van Loggerenberg, A, Vance-Daniel, J, Vancheeswaran, R, Vandeyoon, S, Vankayalapati, P, Vanmali, P, Vansomeren, C, Vara, S, Vardy, S, Varghese, A, Varghese, M, Varney, W, Varnier, G, Varouxaki, A, Varquez, R, Vasadi, V, Vassell, K, Vassell, O, Vasu, V, Vasudevan, V, Vatish, M, Vaughan, S, Vayalaman, H, Vayapooree, D, Vaz, C, Veale, N, Veerasamy, S, Velankar, S, Velauthar, L, Veli, N, Vella, N, Velugupati, A, Velusamy, A, Venables, I, Venditti, M, Venkataramakrishnan, R, Venn, R, Ventilacion, L, Vere, J, Veres, M, Vergnano, S, Verling, W, Verma, A, Vernall, R, Vernon, B, Vertue, M, Verueco, L, Verula, J, Vethanayagam, N, Vettikumaran, S, Veys, L, Vickers, C, Victor, S, Victoria, S, Vidler, J, Vijayakumar, B, Vijayaraghavan Nalini, V, Vilcinskaite, B, Vileito, A, Vilimiene, N, Vinall, L, Vinay, S, Vinayakarao, L, Vincent, O, Vincent, R, Virdee, P, Virgilio, E, Virk, A, Visentin, E, Vitaglione, M, Vithian, K, Vittoria, S, Vivekananthan, S, Vlad, E, Vlies, B, von Oven, L, Vooght, C, Vutipongsatorn, K, Vuylsteke, A, Vyras, E, W Hay, A, Wach, R, Wadams, B, Wadd, S, Waddington, N, Wade, P, Wadsley, J, Wadsworth, K, Wafa, S, Wagstaff, D, Wagstaff, L, Wahab, D, Wahbi, Z, Waheed Adigun, A, Waidyanatha, S, Waite, A, Wake, R, Wakefield, A, Wakeford, W, Wakinshaw, F, Waldeck, E, Walden, A, Walding, L, Waldron, A, Waldron, J, Wales, E, Wali, B, Walker, D, Walker, G, Walker, H, Walker, I, Walker, K, Walker, L, Walker, O, Walker, R, Wallace, G, Wallbutton, R, Wallen, J, Waller, A, Waller, R, Wallis, G, Wallis, L, Wallis, M, Walmsley, E, Walsh, D, Walsh, E, Walsh, L, Walstow, D, Walter, D, Walters, A, Walters, H, Walton, L, Walton, M, Walton, O, Walton, S, Wands, M, Wane, R, Wang, F, Wang, N, Wang, R, Wang, S, Warbrick, D, Warburton, S, Ward, C, Ward, D, Ward, E, Ward, H, Ward, J, Ward, L, Ward, N, Ward, R, Ward, T, Warden, S, Wardere, G, Wardle, S, Wardy, H, Waring, G, Waring, S, Warner, B, Warner, C, Warnock, L, Warran, S, Warren, J, Warren, L, Warren, R, Warren, Y, Warrender, D, Warren-Miell, H, Warwick, G, Wassall, H, Wasson, E, Wastson, E, Watchorn, H, Waterfall, H, Waters, A, Waters, D, Waterstone, M, Watkin, A, Watkins, C, Watkins, E, Watkins, K, Watkins, L, Watson, A, Watson, E, Watson, F, Watson, J, Watson, K, Watson, L, Watson, P, Watson, R, Watters, M, Watterson, D, Watts, D, Watts, J, Watts, M, Waugh, V, Wayman, M, Wazir, A, Weatherhead, M, Weatherly, N, Webb, C, Webb, H, Webb, K, Webb, S, Websdale, C, Webster, D, Webster, I, Webster, J, Webster, T, Wedlin, J, Wee, L, Weerakoon, R, Weerasinghe, T, Weeratunga, J, Weetman, M, Wei, S, Weichert, I, Welch, E, Welch, H, Welch, L, Welch, S, Welham, B, Weller, S, Wellings, L, Wells, B, Wellstead, S, Welsh, B, Welters, I, Welton, R, Wenn, V, Wentworth, L, Wesonga, J, Wesseldine, K, West, J, West, M, West, R, West, S, Western, L, Westhead, R, Weston, H, Westwood, A, Westwood, K, Westwood, S, Wetherill, B, Wheaver, S, Wheeler, H, Whelan, B, Whelband, M, Whileman, A, Whitcher, A, White, A, White, B, White, C, White, D, White, J, White, K, White, M, White, N, White, S, White, T, Whitehead, C, Whitehorn, K, Whitehouse, C, Whitehouse, T, Whiteley, J, Whiteley, L, Whiteley, S, Whitham, R, Whitlingum, G, Whitmore, D, Whittam, L, Whittington, A, Whittle, H, Whittle, R, Wiafe, E, Wiblin, L, Wickens, O, Widdrington, J, Wieboldt, J, Wieringa, H, Wiesender, C, Wiffen, L, Wight, A, Wignall, A, Wignall, C, Wilce, A, Wilcock, D, Wilcock, E, Wilcox, L, Wild, B, Wild, L, Wild, S, Wilde, M, Wilding, L, Wilding, P, Wildsmith, T, Wileman, J, Wiles, K, Wilhelmsen, E, Wiliams, T, Wilkie, J, Wilkin, D, Wilkins, H, Wilkins, J, Wilkins, S, Wilkinson, I, Wilkinson, L, Wilkinson, N, Wilkinson, T, Willetts, S, Williams, A, Williams, C, Williams, D, Williams, E, Williams, G, Williams, H, Williams, J, Williams, K, Williams, M, Williams, R, Williams, S, Williams, T, Williamson, A, Williamson, H, Williamson, R, Willis, E, Willis, H, Willis, J, Wills, L, Willsher, L, Willshire, C, Wilson, A, Wilson, B, Wilson, D, Willson, F, Wilson, I, Willson, J, Wilson, K-A, Wilson, L, Wilson, M, Wilson, T, Win, K, Win, M, Win, T, Win, W, Winckworth, L, Winder, L, Winder, P, Winearl, S, Winmill, H, Winn, S, Winpenny, C, Winslow, H, Winter, H, Winter, J, Winter-Goodwin, B, Winterton, J, Winwood, H, Wischhusen, J, Wisdom, S, Wise, M, Wiselka, M, Wiseman, R, Wiseman, S, Wishart, S, Wishlade, T, Witele, E, Withers, N, Wixted, D, Wodehouse, T, Wolf, W, Wolff, N, Wolffsohn, K, Wolf-Roberts, R, Wolodimeroff, E, Wolstencroft, A, Wong, A, Wong, C, Wong, C H, Wong, E, Wong, J, Wong, K, Wong, M, Wong, N, Wong, S, Wong, T, Wood, A, Wood, D, Wood, F, Wood, G, Wood, H, Wood, J, Wood, L, Wood, M, Wood, S, Wood, T, Woodall, K, Woodfield, R, Woodford, C, Woodford, E, Woodford, J, Woodhead, L, Woodhead, T, Woodland, P, Woodman, M, Woodmansey, S, Woods, C, Woods, J, Woods, K, Woods, S, Woodward, Z, Woolcock, M, Wooldridge, G, Woolf, R, Woollard, C, Woollen, L, Woolley, E, Woolley, J, Woosey, D, Wootton, D, Wootton, J, Worley, D, Worton, S, Wraight, J, Wray, M, Wren, K, Wren, L, Wrey Brown, C, Wright, C, Wright, D, Wright, F, Wright, H, Wright, I, Wright, L, Wright, R, Wright, S, Wright, T, Wroe, C, Wroe, H, Wu, H, Wu, P, Wubetu, J, Wulandari, R, Wurie, S, Wyatt, C, Wyn-Griffiths, F, Wynter, I, Xavier, B, Xhikola, A, Xia, B, Xia, Z, Y Ellis, T, Yacoba, E, Yakubi, M, Yan, M, Yanagisawa, Y, Yang, F, Yang, Y, Yanney, M, Yap, W, Yaqoob, N, Yasmin, S, Yates, B, Yates, D, Yates, E, Yates, H, Yates, M, Yates, T, Ye, J, Yearwood Martin, C, Yein, K, Yeoh, A, Yeung, C, Yew, P, Yewatkar, D, Ylquimiche Melly, L, Ynter, I, Yong, H, Yorke, J, Youens, J, Younes Ibrahim, A, Young, E, Young, G, Young, L, Yousafzar, A, Youssouf, S, Yousuf, A, Yu, C, Yuan, J, Yung, B, Yusef, D, Yusef, S, Yusuf, I, Zafar, A-M, Zagalo, S, Zaher, S, Zahoor, A, Zainab, M, Zak, T, Zaki, K, Zakir, N, Zalewska, K, Zamalloa, A, Zaman, M, Zaman, S, Zamikula, J, Zammit, L, Zammit-Mangion, M, Zawadzka, M, Zebracki, E, Zehnder, D, Zeidan, L, Zeinali, D, Zhang, J, Zhao, X, Zheng, D, Zia, M, Zibdeh, O, Zill-E-Huma, R, Zin, E, Zincone, E, Zindoga, G, Zinkin, E, Zinyemba, V, Zipitis, C, Zitter, L, Zmierczak, A, Zubikarai, G, Zubir, A, Zuhra, N, Zulaikha, R, Zulfikar, S, Zullo, C, and Zuriaga-Alvaro, A
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- 2024
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127. Robust Control Barrier-Value Functions for Safety-Critical Control
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Choi, Jason J., Lee, Donggun, Sreenath, Koushil, Tomlin, Claire J., and Herbert, Sylvia L.
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Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper works towards unifying two popular approaches in the safety control community: Hamilton-Jacobi (HJ) reachability and Control Barrier Functions (CBFs). HJ Reachability has methods for direct construction of value functions that provide safety guarantees and safe controllers, however the online implementation can be overly conservative and/or rely on chattering bang-bang control. The CBF community has methods for safe-guarding controllers in the form of point-wise optimization using quadratic programs (CBF-QP), where the CBF-based safety certificate is used as a constraint. However, finding a valid CBF for a general dynamical system is challenging. This paper unifies these two methods by introducing a new reachability formulation inspired by the structure of CBFs to construct a Control Barrier-Value Function (CBVF). We verify that CBVF is a viscosity solution to a novel Hamilton-Jacobi-Isaacs Variational Inequality and preserves the same safety guarantee as the original reachability formulation. Finally, inspired by the CBF-QP, we propose a QP-based online control synthesis for systems affine in control and disturbance, whose solution is always the CBVF's optimal control signal robust to bounded disturbance. We demonstrate the benefit of using the CBVFs for double-integrator and Dubins car systems by comparing it to previous methods., Comment: IEEE CDC 2021
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- 2021
128. Analyzing Human Models that Adapt Online
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Bajcsy, Andrea, Siththaranjan, Anand, Tomlin, Claire J., and Dragan, Anca D.
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Computer Science - Robotics ,Computer Science - Artificial Intelligence ,Computer Science - Human-Computer Interaction ,Electrical Engineering and Systems Science - Systems and Control - Abstract
Predictive human models often need to adapt their parameters online from human data. This raises previously ignored safety-related questions for robots relying on these models such as what the model could learn online and how quickly could it learn it. For instance, when will the robot have a confident estimate in a nearby human's goal? Or, what parameter initializations guarantee that the robot can learn the human's preferences in a finite number of observations? To answer such analysis questions, our key idea is to model the robot's learning algorithm as a dynamical system where the state is the current model parameter estimate and the control is the human data the robot observes. This enables us to leverage tools from reachability analysis and optimal control to compute the set of hypotheses the robot could learn in finite time, as well as the worst and best-case time it takes to learn them. We demonstrate the utility of our analysis tool in four human-robot domains, including autonomous driving and indoor navigation., Comment: ICRA 2021
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- 2021
129. FaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking
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Chen, Mo, Herbert, Sylvia L., Hu, Haimin, Pu, Ye, Fisac, Jaime F., Bansal, Somil, Han, SooJean, and Tomlin, Claire J.
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Computer Science - Robotics ,Mathematics - Optimization and Control - Abstract
Real-time, guaranteed safe trajectory planning is vital for navigation in unknown environments. However, real-time navigation algorithms typically sacrifice robustness for computation speed. Alternatively, provably safe trajectory planning tends to be too computationally intensive for real-time replanning. We propose FaSTrack, Fast and Safe Tracking, a framework that achieves both real-time replanning and guaranteed safety. In this framework, real-time computation is achieved by allowing any trajectory planner to use a simplified \textit{planning model} of the system. The plan is tracked by the system, represented by a more realistic, higher-dimensional \textit{tracking model}. We precompute the tracking error bound (TEB) due to mismatch between the two models and due to external disturbances. We also obtain the corresponding tracking controller used to stay within the TEB. The precomputation does not require prior knowledge of the environment. We demonstrate FaSTrack using Hamilton-Jacobi reachability for precomputation and three different real-time trajectory planners with three different tracking-planning model pairs., Comment: Published in the IEEE Transactions on Automatic Control
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- 2021
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130. Wait Time Advantage for Transplant Candidates With HIV Who Accept Kidneys From Donors With HIV Under the HOPE Act
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Motter, Jennifer D., Hussain, Sarah, Brown, Diane M., Florman, Sander, Rana, Meenakshi M., Friedman-Moraco, Rachel, Gilbert, Alexander J., Stock, Peter, Mehta, Shikha, Mehta, Sapna A., Stosor, Valentina, Elias, Nahel, Pereira, Marcus R., Haidar, Ghady, Malinis, Maricar, Morris, Michele I., Hand, Jonathan, Aslam, Saima, Schaenman, Joanna M., Baddley, John, Small, Catherine B., Wojciechowski, David, Santos, Carlos A.Q., Blumberg, Emily A., Odim, Jonah, Apewokin, Senu K., Giorgakis, Emmanouil, Bowring, Mary Grace, Werbel, William A., Desai, Niraj M., Tobian, Aaron A.R., Segev, Dorry L., Massie, Allan B., Durand, Christine M., Kusemiju, Oyinkansola, Barnaba, Brittany, Prizzi, Michelle, Liang, Tao, Barnes, Grace Link, Chahoud, Margaret, Wiles, James, Cochran, Willa, Morrison, Michelle, Storm, Kaitlyn, Apte, Anuj, Paredes, Linda, Kuffar, Bahati, Stearns, Quinten, Brown, Nadine, Chang, Amy, Haydel, Brandy M., Pearson, Thomas, Mehta, Aneesh K., Lyon, G. Marshall, Kitchens, William, Huckaby, Jeryl, Elbein, Rivka, Roberson, April, Ferry, Elizabeth, Coakley, Margaret, Akhran, Aleya, Timpone, Joseph, Stucke, Alyssa, Mompoint-Williams, Darnell, Locke, Jayme E., Weldon, Elaina P., Dieter, Rebecca, Klein, Elizabeth, Goudy, Leah, Callegari, Michelle, Gallon, Lorenzo, Hughes, Kailey, Pakstis, Diana Lynn, Silveira, Fernanda, Tomlin, Ricarda, Smith, Angela, Shah, Mita, Mekeel, Kristin, Nguyen, Phirum, Mills, Jeff, Bunnapradist, Suphamai, Gritsch, H. Albin, Moe, Ardis A., Silva, Rosemary, Marrazzo, Ilise D., Muthukumar, Thangamani, Chang, Amy, Hoz, Ricardo La, Hubbard, Jarrett, Mall, Mark, Santos, Carlos, Dunn, Ty, Sawinski, Deirdre, Najdzinowicz, Maryann, Chen, Jeanne M., Nagy, Jamie, and Brigle, Nathaniel
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- 2024
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131. Risk-sensitive safety analysis using Conditional Value-at-Risk
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Chapman, Margaret P., Bonalli, Riccardo, Smith, Kevin M., Yang, Insoon, Pavone, Marco, and Tomlin, Claire J.
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Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper develops a safety analysis method for stochastic systems that is sensitive to the possibility and severity of rare harmful outcomes. We define risk-sensitive safe sets as sub-level sets of the solution to a non-standard optimal control problem, where a random maximum cost is assessed via Conditional Value-at-Risk (CVaR). The objective function represents the maximum extent of constraint violation of the state trajectory, averaged over a given percentage of worst cases. This problem is well-motivated but difficult to solve tractably because the temporal decomposition for CVaR is history-dependent. Our primary theoretical contribution is to derive computationally tractable under-approximations to risk-sensitive safe sets. Our method provides a novel, theoretically guaranteed, parameter-dependent upper bound to the CVaR of a maximum cost without the need to augment the state space. For a fixed parameter value, the solution to only one Markov decision process problem is required to obtain the under-approximations for any family of risk-sensitivity levels. In addition, we propose a second definition for risk-sensitive safe sets and provide a tractable method for their estimation without using a parameter-dependent upper bound. The second definition is expressed in terms of a new coherent risk functional, which is inspired by CVaR. We demonstrate our primary theoretical contribution via numerical examples.
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- 2021
132. Scalable Learning of Safety Guarantees for Autonomous Systems using Hamilton-Jacobi Reachability
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Herbert, Sylvia, Choi, Jason J., Sanjeev, Suvansh, Gibson, Marsalis, Sreenath, Koushil, and Tomlin, Claire J.
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Computer Science - Robotics ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Systems and Control - Abstract
Autonomous systems like aircraft and assistive robots often operate in scenarios where guaranteeing safety is critical. Methods like Hamilton-Jacobi reachability can provide guaranteed safe sets and controllers for such systems. However, often these same scenarios have unknown or uncertain environments, system dynamics, or predictions of other agents. As the system is operating, it may learn new knowledge about these uncertainties and should therefore update its safety analysis accordingly. However, work to learn and update safety analysis is limited to small systems of about two dimensions due to the computational complexity of the analysis. In this paper we synthesize several techniques to speed up computation: decomposition, warm-starting, and adaptive grids. Using this new framework we can update safe sets by one or more orders of magnitude faster than prior work, making this technique practical for many realistic systems. We demonstrate our results on simulated 2D and 10D near-hover quadcopters operating in a windy environment., Comment: The first two authors are co-first authors. ICRA 2021
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- 2021
133. The Computation of Approximate Generalized Feedback Nash Equilibria
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Laine, Forrest, Fridovich-Keil, David, Chiu, Chih-Yuan, and Tomlin, Claire
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Mathematics - Optimization and Control ,Computer Science - Computer Science and Game Theory ,Computer Science - Multiagent Systems ,Computer Science - Robotics - Abstract
We present the concept of a Generalized Feedback Nash Equilibrium (GFNE) in dynamic games, extending the Feedback Nash Equilibrium concept to games in which players are subject to state and input constraints. We formalize necessary and sufficient conditions for (local) GFNE solutions at the trajectory level, which enable the development of efficient numerical methods for their computation. Specifically, we propose a Newton-style method for finding game trajectories which satisfy necessary conditions for an equilibrium, which can then be checked against sufficiency conditions. We show that the evaluation of the necessary conditions in general requires computing a series of nested, implicitly-defined derivatives, which quickly becomes intractable. To this end, we introduce an approximation to the necessary conditions which is amenable to efficient evaluation, and in turn, computation of solutions. We term the solutions to the approximate necessary conditions Generalized Feedback Quasi-Nash Equilibria (GFQNE), and we introduce numerical methods for their computation. In particular, we develop a Sequential Linear-Quadratic Game approach, in which a LQ local approximation of the game is solved at each iteration. The development of this method relies on the ability to compute a GFNE to inequality- and equality-constrained LQ games, and therefore specific methods for the solution of these special cases are developed in detail. We demonstrate the effectiveness of the proposed solution approach on a dynamic game arising in an autonomous driving application.
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- 2021
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134. Certifiable Deep Learning for Reachability Using a New Lipschitz Continuous Value Function.
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Jingqi Li, Donggun Lee, Jaewon Lee, Kris Shengjun Dong, Somayeh Sojoudi, and Claire J. Tomlin
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- 2024
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135. Understanding the Dependence of Perception Model Competency on Regions in an Image.
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Sara Pohland and Claire J. Tomlin
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- 2024
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136. Effects of dynamic power electronic load models on power systems analysis using ZIP-E loads.
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Gabriel E. Colon-Reyes, Reid Dye, Claire J. Tomlin, and Duncan Callaway
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- 2024
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137. Autonomous Evaluation and Refinement of Digital Agents.
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Jiayi Pan, Yichi Zhang, Nicholas Tomlin, Yifei Zhou, Sergey Levine, and Alane Suhr
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- 2024
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138. Unfamiliar Finetuning Examples Control How Language Models Hallucinate.
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Katie Kang, Eric Wallace, Claire J. Tomlin, Aviral Kumar, and Sergey Levine
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- 2024
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139. Efficacy of Language Model Self-Play in Non-Zero-Sum Games.
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Austen Liao, Nicholas Tomlin, and Dan Klein
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- 2024
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140. Intent Demonstration in General-Sum Dynamic Games via Iterative Linear-Quadratic Approximations.
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Jingqi Li, Anand Siththaranjan, Somayeh Sojoudi, Claire J. Tomlin, and Andrea Bajcsy
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- 2024
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141. The computation of approximate feedback Stackelberg equilibria in multi-player nonlinear constrained dynamic games.
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Jingqi Li, Somayeh Sojoudi, Claire J. Tomlin, and David Fridovich-Keil
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- 2024
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142. Voronoi Progressive Widening: Efficient Online Solvers for Continuous State, Action, and Observation POMDPs
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Lim, Michael H., Tomlin, Claire J., and Sunberg, Zachary N.
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Robotics ,Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper introduces Voronoi Progressive Widening (VPW), a generalization of Voronoi optimistic optimization (VOO) and action progressive widening to partially observable Markov decision processes (POMDPs). Tree search algorithms can use VPW to effectively handle continuous or hybrid action spaces by efficiently balancing local and global action searching. This paper proposes two VPW-based algorithms and analyzes them from theoretical and simulation perspectives. Voronoi Optimistic Weighted Sparse Sampling (VOWSS) is a theoretical tool that justifies VPW-based online solvers, and it is the first algorithm with global convergence guarantees for continuous state, action, and observation POMDPs. Voronoi Optimistic Monte Carlo Planning with Observation Weighting (VOMCPOW) is a versatile and efficient algorithm that consistently outperforms state-of-the-art POMDP algorithms in several simulation experiments.
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- 2020
143. Interferometric Constraints on Spacelike Coherent Rotational Fluctuations
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Richardson, Jonathan W., Kwon, Ohkyung, Gustafson, H. Richard, Hogan, Craig, Kamai, Brittany L., McCuller, Lee P., Meyer, Stephan S., Stoughton, Chris, Tomlin, Raymond E., and Weiss, Rainer
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General Relativity and Quantum Cosmology ,High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
Precision measurements are reported of the cross-spectrum of rotationally-induced differential position displacements in a pair of colocated 39 m long, high power Michelson interferometers. One arm of each interferometer is bent $90^{\circ}$ near its midpoint to obtain sensitivity to rotations about an axis normal to the plane of the instrument. The instrument achieves quantum-limited sensing of spatially-correlated signals in a broad frequency band extending beyond the 3.9 MHz inverse light travel time of the apparatus. For stationary signals with bandwidth $\Delta f > 10\;\mathrm{kHz}$, the sensitivity to rotation-induced strain $h$ of classical or exotic origin surpasses $\mathrm{CSD}_{\delta h} < t_P / 2$, where $t_P = 5.39 \times 10^{-44}\;\mathrm{s}$ is the Planck time. This measurement is used to constrain a semiclassical model of nonlocally coherent rotational degrees of freedom of spacetime, which have been conjectured to emerge in holographic quantum geometry but are not present in a classical metric., Comment: 9 pages, 4 figures. PRL accepted manuscript
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- 2020
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144. Gaussian Process-based Min-norm Stabilizing Controller for Control-Affine Systems with Uncertain Input Effects and Dynamics
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Castañeda, Fernando, Choi, Jason J., Zhang, Bike, Tomlin, Claire J., and Sreenath, Koushil
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Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Machine Learning ,Mathematics - Optimization and Control - Abstract
This paper presents a method to design a min-norm Control Lyapunov Function (CLF)-based stabilizing controller for a control-affine system with uncertain dynamics using Gaussian Process (GP) regression. In order to estimate both state and input-dependent model uncertainty, we propose a novel compound kernel that captures the control-affine nature of the problem. Furthermore, by the use of GP Upper Confidence Bound analysis, we provide probabilistic bounds of the regression error, leading to the formulation of a CLF-based stability chance constraint which can be incorporated in a min-norm optimization problem. We show that this resulting optimization problem is convex, and we call it Gaussian Process-based Control Lyapunov Function Second-Order Cone Program (GP-CLF-SOCP). The data-collection process and the training of the GP regression model are carried out in an episodic learning fashion. We validate the proposed algorithm and controller in numerical simulations of an inverted pendulum and a kinematic bicycle model, resulting in stable trajectories which are very similar to the ones obtained if we actually knew the true plant dynamics., Comment: The first two authors contributed equally. To appear at the 2021 American Control Conference (ACC)
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- 2020
145. Testing for Typicality with Respect to an Ensemble of Learned Distributions
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Laine, Forrest and Tomlin, Claire
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Computer Science - Machine Learning - Abstract
Methods of performing anomaly detection on high-dimensional data sets are needed, since algorithms which are trained on data are only expected to perform well on data that is similar to the training data. There are theoretical results on the ability to detect if a population of data is likely to come from a known base distribution, which is known as the goodness-of-fit problem. One-sample approaches to this problem offer significant computational advantages for online testing, but require knowing a model of the base distribution. The ability to correctly reject anomalous data in this setting hinges on the accuracy of the model of the base distribution. For high dimensional data, learning an accurate-enough model of the base distribution such that anomaly detection works reliably is very challenging, as many researchers have noted in recent years. Existing methods for the one-sample goodness-of-fit problem do not account for the fact that a model of the base distribution is learned. To address that gap, we offer a theoretically motivated approach to account for the density learning procedure. In particular, we propose training an ensemble of density models, considering data to be anomalous if the data is anomalous with respect to any member of the ensemble. We provide a theoretical justification for this approach, proving first that a test on typicality is a valid approach to the goodness-of-fit problem, and then proving that for a correctly constructed ensemble of models, the intersection of typical sets of the models lies in the interior of the typical set of the base distribution. We present our method in the context of an example on synthetic data in which the effects we consider can easily be seen., Comment: Written in October 2019
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- 2020
146. Multi-Hypothesis Interactions in Game-Theoretic Motion Planning
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Laine, Forrest, Fridovich-Keil, David, Chiu, Chih-Yuan, and Tomlin, Claire
- Subjects
Computer Science - Robotics ,Computer Science - Multiagent Systems - Abstract
We present a novel method for handling uncertainty about the intentions of non-ego players in dynamic games, with application to motion planning for autonomous vehicles. Equilibria in these games explicitly account for interaction among other agents in the environment, such as drivers and pedestrians. Our method models the uncertainty about the intention of other agents by constructing multiple hypotheses about the objectives and constraints of other agents in the scene. For each candidate hypothesis, we associate a Bernoulli random variable representing the probability of that hypothesis, which may or may not be independent of the probability of other hypotheses. We leverage constraint asymmetries and feedback information patterns to incorporate the probabilities of hypotheses in a natural way. Specifically, increasing the probability associated with a given hypothesis from $0$ to $1$ shifts the responsibility of collision avoidance from the hypothesized agent to the ego agent. This method allows the generation of interactive trajectories for the ego agent, where the level of assertiveness or caution that the ego exhibits is directly related to the easy-to-model uncertainty it maintains about the scene., Comment: For associated mp4 file, see https://youtu.be/x7VtYDrWTWM
- Published
- 2020
147. Encoding Defensive Driving as a Dynamic Nash Game
- Author
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Chiu, Chih-Yuan, Fridovich-Keil, David, and Tomlin, Claire J.
- Subjects
Computer Science - Robotics ,Electrical Engineering and Systems Science - Systems and Control - Abstract
Robots deployed in real-world environments should operate safely in a robust manner. In scenarios where an "ego" agent navigates in an environment with multiple other "non-ego" agents, two modes of safety are commonly proposed -- adversarial robustness and probabilistic constraint satisfaction. However, while the former is generally computationally intractable and leads to overconservative solutions, the latter typically relies on strong distributional assumptions and ignores strategic coupling between agents. To avoid these drawbacks, we present a novel formulation of robustness within the framework of general-sum dynamic game theory, modeled on defensive driving. More precisely, we prepend an adversarial phase to the ego agent's cost function. That is, we prepend a time interval during which other agents are assumed to be temporarily distracted, in order to render the ego agent's equilibrium trajectory robust against other agents' potentially dangerous behavior during this time. We demonstrate the effectiveness of our new formulation in encoding safety via multiple traffic scenarios., Comment: Accepted to ICRA 2021
- Published
- 2020
148. DeepReach: A Deep Learning Approach to High-Dimensional Reachability
- Author
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Bansal, Somil and Tomlin, Claire
- Subjects
Computer Science - Robotics ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Systems and Control - Abstract
Hamilton-Jacobi (HJ) reachability analysis is an important formal verification method for guaranteeing performance and safety properties of dynamical control systems. Its advantages include compatibility with general nonlinear system dynamics, formal treatment of bounded disturbances, and the ability to deal with state and input constraints. However, it involves solving a PDE, whose computational and memory complexity scales exponentially with respect to the number of state variables, limiting its direct use to small-scale systems. We propose DeepReach, a method that leverages new developments in sinusoidal networks to develop a neural PDE solver for high-dimensional reachability problems. The computational requirements of DeepReach do not scale directly with the state dimension, but rather with the complexity of the underlying reachable tube. DeepReach achieves comparable results to the state-of-the-art reachability methods, does not require any explicit supervision for the PDE solution, can easily handle external disturbances, adversarial inputs, and system constraints, and also provides a safety controller for the system. We demonstrate DeepReach on a 9D multi-vehicle collision problem, and a 10D narrow passage problem, motivated by autonomous driving applications.
- Published
- 2020
149. Approximate Solutions to a Class of Reachability Games
- Author
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Fridovich-Keil, David and Tomlin, Claire J.
- Subjects
Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Computer Science and Game Theory ,Computer Science - Robotics - Abstract
In this paper, we present a method for finding approximate Nash equilibria in a broad class of reachability games. These games are often used to formulate both collision avoidance and goal satisfaction. Our method is computationally efficient, running in real-time for scenarios involving multiple players and more than ten state dimensions. The proposed approach forms a family of increasingly exact approximations to the original game. Our results characterize the quality of these approximations and show operation in a receding horizon, minimally-invasive control context. Additionally, as a special case, our method reduces to local gradient-based optimization in the single-player (optimal control) setting, for which a wide variety of efficient algorithms exist., Comment: Conference paper at ICRA 2021
- Published
- 2020
150. Revisiting Entropy Rate Constancy in Text.
- Author
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Vivek Verma, Nicholas Tomlin, and Dan Klein
- Published
- 2023
- Full Text
- View/download PDF
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