102 results on '"Pajic, Miroslav"'
Search Results
2. At home adaptive dual target deep brain stimulation in Parkinson's disease with proportional control.
- Author
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Schmidt, Stephen L, Chowdhury, Afsana H, Mitchell, Kyle T, Peters, Jennifer J, Gao, Qitong, Lee, Hui-Jie, Genty, Katherine, Chow, Shein-Chung, Grill, Warren M, Pajic, Miroslav, and Turner, Dennis A
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SUBTHALAMIC nucleus ,DEEP brain stimulation ,PARKINSON'S disease ,ESSENTIAL tremor ,PREVENTIVE medicine ,GLOBUS pallidus ,SYMPTOMS - Abstract
Continuous deep brain stimulation (cDBS) of the subthalamic nucleus (STN) or globus pallidus is an effective treatment for the motor symptoms of Parkinson's disease. The relative benefit of one region over the other is of great interest but cannot usually be compared in the same patient. Simultaneous DBS of both regions may synergistically increase the therapeutic benefit. Continuous DBS is limited by a lack of responsiveness to dynamic, fluctuating symptoms intrinsic to the disease. Adaptive DBS (aDBS) adjusts stimulation in response to biomarkers to improve efficacy, side effects, and efficiency. We combined bilateral DBS of both STN and globus pallidus (dual target DBS) in a prospective within-participant, clinical trial in six patients with Parkinson's disease (n = 6, 55–65 years, n = 2 females). Dual target cDBS was tested for Parkinson's disease symptom control annually over 2 years, measured by motor rating scales, on time without dyskinesia, and medication reduction. Random amplitude experiments probed system dynamics to estimate parameters for aDBS. We then implemented proportional-plus-integral aDBS using a novel distributed (off-implant) architecture. In the home setting, we collected tremor and dyskinesia scores as well as individualized β and DBS amplitudes. Dual target cDBS reduced motor symptoms as measured by Unified Parkinson's Disease Rating Scale (UPDRS) to a greater degree than either region alone (P < 0.05, linear mixed model) in the cohort. The amplitude of β-oscillations in the STN correlated to the speed of hand grasp movements for five of six participants (P < 0.05, Pearson correlation). Random amplitude experiments provided insight into temporal windowing to avoid stimulation artefacts and demonstrated a correlation between STN β amplitude and DBS amplitude. Proportional plus integral control of aDBS reduced average power, while preserving UPDRS III scores in the clinic (P = 0.28, Wilcoxon signed rank), and tremor and dyskinesia scores during blinded testing at home (n = 3 , P > 0.05, Wilcoxon ranked sum). In the home setting, DBS power reductions were slight but significant. Dual target cDBS may offer an improvement in treatment of motor symptoms of Parkinson's disease over DBS of either the STN or globus pallidus alone. When combined with proportional plus integral aDBS, stimulation power may be reduced, while preserving the increased benefit of dual target DBS. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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3. Athena – The NSF AI Institute for Edge Computing.
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Chen, Yiran, Banerjee, Suman, Daily, Shaundra, Krolik, Jeffery, Li, Hai, Limbrick, Daniel, Pajic, Miroslav, Runton, Rajashi, and Zhong, Lin
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ARTIFICIAL intelligence ,EDGE computing ,NEXT generation networks ,COMPUTER systems ,CYBER physical systems ,MACHINE learning - Abstract
The National Science Foundation (NSF) Artificial Intelligence (AI) Institute for Edge Computing Leveraging Next Generation Networks (Athena) seeks to foment a transformation in modern edge computing by advancing AI foundations, computing paradigms, networked computing systems, and edge services and applications from a completely new computing perspective. Led by Duke University, Athena leverages revolutionary developments in computer systems, machine learning, networked computing systems, cyber‐physical systems, and sensing. Members of Athena form a multidisciplinary team from eight universities. Athena organizes its research activities under four interrelated thrusts supporting edge computing: Foundational AI, Computer Systems, Networked Computing Systems, and Services and Applications, which constitute an ambitious and comprehensive research agenda. The research tasks of Athena will focus on developing AI‐driven next‐generation technologies for edge computing and new algorithmic and practical foundations of AI and evaluating the research outcomes through a combination of analytical, experimental, and empirical instruments, especially with target use‐inspired research. The researchers of Athena demonstrate a cohesive effort by synergistically integrating the research outcomes from the four thrusts into three pillars: Edge Computing AI Systems, Collaborative Extended Reality (XR), and Situational Awareness and Autonomy. Athena is committed to a robust and comprehensive suite of educational and workforce development endeavors alongside its domestic and international collaboration and knowledge transfer efforts with external stakeholders that include both industry and community partnerships. [ABSTRACT FROM AUTHOR]
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- 2024
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4. A hybrid stochastic game for secure control of cyber-physical systems
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Miao, Fei, Zhu, Quanyan, Pajic, Miroslav, and Pappas, George J.
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- 2018
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5. Individual Treatment Effects in Extreme Regimes
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Aloui, Ahmed, Hasan, Ali, Ng, Yuting, Pajic, Miroslav, and Tarokh, Vahid
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Methodology (stat.ME) ,FOS: Computer and information sciences ,Computer Science - Machine Learning ,Statistics - Machine Learning ,Machine Learning (stat.ML) ,Statistics - Methodology ,Machine Learning (cs.LG) - Abstract
Understanding individual treatment effects in extreme regimes is important for characterizing risks associated with different interventions. This is hindered by the fact that extreme regime data may be hard to collect, as it is scarcely observed in practice. In addressing this issue, we propose a new framework for estimating the individual treatment effect in extreme regimes (ITE$_2$). Specifically, we quantify this effect by the changes in the tail decay rates of potential outcomes in the presence or absence of the treatment. Subsequently, we establish conditions under which ITE$_2$ may be calculated and develop algorithms for its computation. We demonstrate the efficacy of our proposed method on various synthetic and semi-synthetic datasets.
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- 2023
6. Robust Reinforcement Learning through Efficient Adversarial Herding
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Dong, Juncheng, Hsu, Hao-Lun, Gao, Qitong, Tarokh, Vahid, and Pajic, Miroslav
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Computer Science - Robotics ,Artificial Intelligence (cs.AI) ,Computer Science - Artificial Intelligence ,Robotics (cs.RO) ,Machine Learning (cs.LG) - Abstract
Although reinforcement learning (RL) is considered the gold standard for policy design, it may not always provide a robust solution in various scenarios. This can result in severe performance degradation when the environment is exposed to potential disturbances. Adversarial training using a two-player max-min game has been proven effective in enhancing the robustness of RL agents. In this work, we extend the two-player game by introducing an adversarial herd, which involves a group of adversaries, in order to address ($\textit{i}$) the difficulty of the inner optimization problem, and ($\textit{ii}$) the potential over pessimism caused by the selection of a candidate adversary set that may include unlikely scenarios. We first prove that adversarial herds can efficiently approximate the inner optimization problem. Then we address the second issue by replacing the worst-case performance in the inner optimization with the average performance over the worst-$k$ adversaries. We evaluate the proposed method on multiple MuJoCo environments. Experimental results demonstrate that our approach consistently generates more robust policies.
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- 2023
7. High Dimensional Geometry and Limitations in System Identification
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Naeem, Muhammad Abdullah and Pajic, Miroslav
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FOS: Mathematics ,FOS: Electrical engineering, electronic engineering, information engineering ,Mathematics - Statistics Theory ,Statistics Theory (math.ST) ,Systems and Control (eess.SY) ,Electrical Engineering and Systems Science - Systems and Control - Abstract
We study the problem of identification of linear dynamical system from a single trajectory, via excitations of isotropic Gaussian. In stark contrast with previously reported results, Ordinary Least Squares (OLS) estimator for even \emph{stable} dynamical system contains non-vanishing error in \emph{high dimensions}; which stems from the fact that realizations of non-diagonalizable dynamics can have strong \emph{spatial correlations} and a variance, of order $O(e^{n})$, where $n$ is the dimension of the underlying state space. Employing \emph{concentration of measure phenomenon}, in particular tensorization of \emph{Talagrands inequality} for random dynamical systems we show that observed trajectory of dynamical system of length-$N$ can have a variance of order $O(e^{nN})$. Consequently, showing some or most of the $n$ distances between an $N-$ dimensional random vector and an $(n-1)$ dimensional hyperplane in $\mathbb{R}^{N}$ can be close to zero with positive probability and these estimates become stronger in high dimensions and more iterations via \emph{Isoperimetry}. \emph{Negative second moment identity}, along with distance estimates give a control on all the singular values of \emph{Random matrix} of data, revealing limitations of OLS for stable non-diagonalizable and explosive diagonalizable systems.
- Published
- 2023
8. Partial-Information, Longitudinal Cyber Attacks on LiDAR in Autonomous Vehicles
- Author
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Hallyburton, R. Spencer, Zhang, Qingzhao, Mao, Z. Morley, and Pajic, Miroslav
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FOS: Computer and information sciences ,Computer Science - Cryptography and Security ,FOS: Electrical engineering, electronic engineering, information engineering ,Systems and Control (eess.SY) ,Cryptography and Security (cs.CR) ,Electrical Engineering and Systems Science - Systems and Control - Abstract
What happens to an autonomous vehicle (AV) if its data are adversarially compromised? Prior security studies have addressed this question through mostly unrealistic threat models, with limited practical relevance, such as white-box adversarial learning or nanometer-scale laser aiming and spoofing. With growing evidence that cyber threats pose real, imminent danger to AVs and cyber-physical systems (CPS) in general, we present and evaluate a novel AV threat model: a cyber-level attacker capable of disrupting sensor data but lacking any situational awareness. We demonstrate that even though the attacker has minimal knowledge and only access to raw data from a single sensor (i.e., LiDAR), she can design several attacks that critically compromise perception and tracking in multi-sensor AVs. To mitigate vulnerabilities and advance secure architectures in AVs, we introduce two improvements for security-aware fusion: a probabilistic data-asymmetry monitor and a scalable track-to-track fusion of 3D LiDAR and monocular detections (T2T-3DLM); we demonstrate that the approaches significantly reduce attack effectiveness. To support objective safety and security evaluations in AVs, we release our security evaluation platform, AVsec, which is built on security-relevant metrics to benchmark AVs on gold-standard longitudinal AV datasets and AV simulators.
- Published
- 2023
9. Variational Latent Branching Model for Off-Policy Evaluation
- Author
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Gao, Qitong, Gao, Ge, Chi, Min, and Pajic, Miroslav
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Artificial Intelligence ,Statistics - Machine Learning ,Machine Learning (stat.ML) ,Machine Learning (cs.LG) - Abstract
Model-based methods have recently shown great potential for off-policy evaluation (OPE); offline trajectories induced by behavioral policies are fitted to transitions of Markov decision processes (MDPs), which are used to rollout simulated trajectories and estimate the performance of policies. Model-based OPE methods face two key challenges. First, as offline trajectories are usually fixed, they tend to cover limited state and action space. Second, the performance of model-based methods can be sensitive to the initialization of their parameters. In this work, we propose the variational latent branching model (VLBM) to learn the transition function of MDPs by formulating the environmental dynamics as a compact latent space, from which the next states and rewards are then sampled. Specifically, VLBM leverages and extends the variational inference framework with the recurrent state alignment (RSA), which is designed to capture as much information underlying the limited training data, by smoothing out the information flow between the variational (encoding) and generative (decoding) part of VLBM. Moreover, we also introduce the branching architecture to improve the model's robustness against randomly initialized model weights. The effectiveness of the VLBM is evaluated on the deep OPE (DOPE) benchmark, from which the training trajectories are designed to result in varied coverage of the state-action space. We show that the VLBM outperforms existing state-of-the-art OPE methods in general., Accepted to ICLR 2023
- Published
- 2023
10. Transportation-Inequalities, Lyapunov Stability and Sampling for Dynamical Systems on Continuous State Space
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Naeem, Muhammad Abdullah and Pajic, Miroslav
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Statistics - Machine Learning ,Information Theory (cs.IT) ,Computer Science - Information Theory ,FOS: Electrical engineering, electronic engineering, information engineering ,Machine Learning (stat.ML) ,Systems and Control (eess.SY) ,Electrical Engineering and Systems Science - Systems and Control ,Machine Learning (cs.LG) - Abstract
We study the concentration phenomenon for discrete-time random dynamical systems with an unbounded state space. We develop a heuristic approach towards obtaining exponential concentration inequalities for dynamical systems using an entirely functional analytic framework. We also show that existence of exponential-type Lyapunov function, compared to the purely deterministic setting, not only implies stability but also exponential concentration inequalities for sampling from the stationary distribution, via \emph{transport-entropy inequality} (T-E). These results have significant impact in \emph{reinforcement learning} (RL) and \emph{controls}, leading to exponential concentration inequalities even for unbounded observables, while neither assuming reversibility nor exact knowledge of random dynamical system (assumptions at heart of concentration inequalities in statistical mechanics and Markov diffusion processes).
- Published
- 2022
11. Attack-resilient state estimation with intermittent data authentication
- Author
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Khazraei, Amir and Pajic, Miroslav
- Published
- 2022
- Full Text
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12. Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly
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Jakovljevic, Zivana, Petrovic, Petar B., Mikovic, Vladimir Dj., and Pajic, Miroslav
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- 2014
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13. Closed-loop verification of medical devices with model abstraction and refinement
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Jiang, Zhihao, Pajic, Miroslav, Alur, Rajeev, and Mangharam, Rahul
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- 2014
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14. Learning-Based Vulnerability Analysis of Cyber-Physical Systems
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Khazraei, Amir, Hallyburton, Spencer, Qitong Gao, Wang, Yu, and Pajic, Miroslav
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Computer Science - Cryptography and Security ,FOS: Electrical engineering, electronic engineering, information engineering ,Systems and Control (eess.SY) ,Cryptography and Security (cs.CR) ,Electrical Engineering and Systems Science - Systems and Control ,Machine Learning (cs.LG) - Abstract
This work focuses on the use of deep learning for vulnerability analysis of cyber-physical systems (CPS). Specifically, we consider a control architecture widely used in CPS (e.g., robotics), where the low-level control is based on e.g., the extended Kalman filter (EKF) and an anomaly detector. To facilitate analyzing the impact potential sensing attacks could have, our objective is to develop learning-enabled attack generators capable of designing stealthy attacks that maximally degrade system operation. We show how such problem can be cast within a learning-based grey-box framework where parts of the runtime information are known to the attacker, and introduce two models based on feed-forward neural networks (FNN); both models are trained offline, using a cost function that combines the attack effects on the estimation error and the residual signal used for anomaly detection, so that the trained models are capable of recursively generating such effective sensor attacks in real-time. The effectiveness of the proposed methods is illustrated on several case studies.
- Published
- 2021
15. Security Analysis for Distributed IoT-Based Industrial Automation.
- Author
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Lesi, Vuk, Jakovljevic, Zivana, and Pajic, Miroslav
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INDUSTRIAL robots ,PETRI nets ,SEMANTICS ,INTERNET of things ,PROGRAMMING languages ,COMPUTER firmware ,BILEVEL programming - Abstract
Internet of Things (IoT) technologies enable development of reconfigurable manufacturing systems—a new generation of modularized industrial equipment suitable for highly customized manufacturing. Sequential control in these systems is largely based on discrete events, whereas their formal execution semantics is specified as control interpreted Petri nets (CIPN). Despite industry-wide use of programming languages based on the CIPN formalism, formal verification of such control applications in the presence of adversarial activity is not supported. Consequently, in this article, we introduce security-aware modeling and verification techniques for CIPN-based sequential control applications. Specifically, we show how CIPN models of networked industrial IoT controllers can be transformed into time Petri net (TPN)-based models and composed with plant and security-aware channel models in order to enable system-level verification of safety properties in the presence of network-based attacks. Additionally, we introduce realistic channel-specific attack models that capture adversarial behavior using nondeterminism. Moreover, we show how verification results can be utilized to introduce security patches and facilitate design of attack detectors that improve system resiliency and enable satisfaction of critical safety properties. Finally, we evaluate our framework on an industrial case study. Note to Practitioners—Our main goal is to provide formal security guarantees for distributed sequential controllers. Specifically, we target smart automation controllers geared toward Industrial IoT applications that are typically programed in C/C++ and are running applications originally designed in, for example, GRAFCET (IEC 60848)/SFC (IEC 61131-3) automation programming languages. Since existing tools for the design of distributed automation do not support system-level verification of relevant safety properties, we show how security-aware transceiver and communication models can be developed and composed with distributed controller models. Then, we show how existing tools for verification of time Petri nets can be used to verify relevant properties including safety and liveness of the distributed automation system in the presence of network-based attacks. To provide an end-to-end analysis as well as security patching, results of our analysis can be used to deploy suitable firmware updates during the stage when executable code for target controllers (e.g., in C/C++) is generated based on GRAFCET/SFC control models. We also show that security guarantees can be improved as the relevant safety/liveness properties can be verified after corresponding security patches are deployed. Finally, we show applicability of our framework on a realistic distributed pneumatic manipulator. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
16. Formal Synthesis of Adaptive Droplet Routing for MEDA Biochips.
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Elfar, Mahmoud, Liang, Tung-Che, Chakrabarty, Krishnendu, and Pajic, Miroslav
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BIOCHIPS ,MICROELECTRODES ,DNA sequencing ,DROPLETS ,REAL-time control ,BIOLOGICAL assay ,STOCHASTIC models - Abstract
A digital microfluidic biochip (DMFB) enables the miniaturization of immunoassays, point-of-care clinical diagnostics, and DNA sequencing. A recent generation of DMFBs uses a microelectrode-dot-array (MEDA) architecture, which provides fine-grained control of droplets and real-time droplet sensing using CMOS technology. However, microelectrodes in a MEDA biochip can degrade due to charge trapping when they are repeatedly charged and discharged during bioassay execution; such degradation leads to the failure of microelectrodes and erroneous bioassay outcomes. To address this problem, we first introduce a new microelectrode-cell design such that we can obtain the health status of all the microelectrodes in a MEDA biochip by employing the inherent sensing mechanism. Next, we present a stochastic game-based model for droplet manipulation, and a formal synthesis method for droplet routing that can dynamically change droplet transportation routes. This adaptation is based on the real-time health information obtained from microelectrodes. Comprehensive simulation results for four real-life bioassays show that our method increases the likelihood of successful bioassay completion with negligible impact on time-to-results. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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17. Spatio-Temporal Techniques for Anti-Jamming in Embedded Wireless Networks
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Pajic, Miroslav and Mangharam, Rahul
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- 2010
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18. Context-Aware Temporal Logic for Probabilistic Systems
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Elfar, Mahmoud, Wang, Yu, and Pajic, Miroslav
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FOS: Computer and information sciences ,Computer Science - Logic in Computer Science ,Formal Languages and Automata Theory (cs.FL) ,Computer Science - Formal Languages and Automata Theory ,Logic in Computer Science (cs.LO) - Abstract
In this paper, we introduce the context-aware probabilistic temporal logic (CAPTL) that provides an intuitive way to formalize system requirements by a set of PCTL objectives with a context-based priority structure. We formally present the syntax and semantics of CAPTL and propose a synthesis algorithm for CAPTL requirements. We also implement the algorithm based on the PRISM-games model checker. Finally, we demonstrate the usage of CAPTL on two case studies: a robotic task planning problem, and synthesizing error-resilient scheduler for micro-electrode-dot-array digital microfluidic biochips.
- Published
- 2020
19. Learning Expected Reward for Switched Linear Control Systems: A Non-Asymptotic View
- Author
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Naeem, Muhammad Abdullah and Pajic, Miroslav
- Subjects
FOS: Computer and information sciences ,Computer Science - Machine Learning ,Probability (math.PR) ,FOS: Mathematics ,FOS: Electrical engineering, electronic engineering, information engineering ,Systems and Control (eess.SY) ,Electrical Engineering and Systems Science - Systems and Control ,Mathematics - Probability ,Machine Learning (cs.LG) - Abstract
In this work, we show existence of invariant ergodic measure for switched linear dynamical systems (SLDSs) under a norm-stability assumption of system dynamics in some unbounded subset of $\mathbb{R}^{n}$. Consequently, given a stationary Markov control policy, we derive non-asymptotic bounds for learning expected reward (w.r.t the invariant ergodic measure our closed-loop system mixes to) from time-averages using Birkhoff's Ergodic Theorem. The presented results provide a foundation for deriving non-asymptotic analysis for average reward-based optimal control of SLDSs. Finally, we illustrate the presented theoretical results in two case-studies.
- Published
- 2020
20. Chronic dual target continuous and externally controlled adaptive deep brain stimulation with Summit RC+S are equally effective for motor symptom control in Parkinson disease
- Author
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Mitchell, Kyle, Schmidt, Stephen, Pajic, Miroslav, Chowdhury, Afsana, Gao, Qitong, Grill, Warren, Lee, Hui-Jie, Cooney, Jeffrey, Peters, Jennifer, and Turner, Dennis
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- 2023
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21. Statistical Verification of Hyperproperties for Cyber-Physical System
- Author
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Wang, Yu, Zarei, Mojtaba, Bonakdarpour, Borzoo, and Pajic, Miroslav
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FOS: Computer and information sciences ,Computer Science - Logic in Computer Science ,Logic in Computer Science (cs.LO) - Abstract
Many important properties of cyber-physical systems (CPS) are defined upon the relationship between multiple executions simultaneously in continuous time. Examples include probabilistic fairness and sensitivity to modeling errors (i.e., parameters changes) for real-valued signals. These requirements can only be specified by hyperproperties. In this work, we focus on verifying probabilistic hyperproperties for CPS. To cover a wide range of modeling formalisms, we first propose a general model of probabilistic uncertain systems (PUSs) that unify commonly studied CPS models such as continuous-time Markov chains (CTMCs) and probabilistically parametrized Hybrid I/O Automata. To formally specify hyperproperties, we propose a new temporal logic, hyper probabilistic signal temporal logic (HyperPSTL) that serves as a hyper and probabilistic version of the conventional signal temporal logic (STL). Considering complexity of real-world systems that can be captured as PUSs, we adopt a statistical model checking (SMC) approach for their verification. We develop a new SMC technique based on the direct computation of the significance levels of statistical assertions for HyperPSTL specifications, which requires no a priori knowledge on the indifference margin. Then, we introduce SMC algorithms for HyperPSTL specifications on the joint probabilistic distribution of multiple paths, as well as specifications with nested probabilistic operators quantifying different paths, which cannot be handled by existing SMC algorithms. Finally, we show the effectiveness of our SMC algorithms on CPS benchmarks with varying levels of complexity, including the Toyota Powertrain Control~System.
- Published
- 2019
22. Extending the Lifetime of MEDA Biochips by Selective Sensing on Microelectrodes.
- Author
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Liang, Tung-Che, Zhong, Zhanwei, Pajic, Miroslav, and Chakrabarty, Krishnendu
- Subjects
BIOCHIPS ,REAL-time control ,MICROELECTRODES ,POINT-of-care testing ,NUCLEOTIDE sequence ,BIOLOGICAL assay - Abstract
A digital microfluidic biochip (DMFB) enables miniaturization of immunoassays, point-of-care clinical diagnostics, and DNA sequencing. A recent generation of DMFBs uses a micro-electrode-dot-array (MEDA) architecture, which provides fine-grained control of droplets and real-time droplet sensing using the CMOS technology. However, microelectrodes in a MEDA biochip degrade when they are charged and discharged frequently during bioassay execution. In this article, we first make the key observation that the droplet-sensing operations contribute up to 94% of all microelectrode actuation in MEDA. Consequently, to reduce the number of droplet-sensing operations, we present a new microelectrode cell (MC) design as well as a selective-sensing method such that only a small fraction of microelectrodes perform droplet sensing during bioassay execution. The selection of microelectrodes that need to perform the droplet sensing is based on an analysis of experimental data. A comprehensive set of simulation results show that the total number of droplet-sensing operations is reduced to only 0.7%, which prolongs the lifespan of a MEDA biochip by $11\times $ without any impact on bioassay time-to-response. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
23. A Moving-Horizon Hybrid Stochastic Game for Secure Control of Cyber-Physical Systems
- Author
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Miao, Fei, Zhu, Quanyan, Pajic, Miroslav, and Pappas, George J.
- Subjects
FOS: Computer and information sciences ,Computer Science - Computer Science and Game Theory ,Computer Science and Game Theory (cs.GT) - Abstract
In this paper, we establish a zero-sum, hybrid state stochastic game model for designing defense policies for cyber-physical systems against different types of attacks. With the increasingly integrated properties of cyber-physical systems (CPS) today, security is a challenge for critical infrastructures. Though resilient control and detecting techniques for a specific model of attack have been proposed, to analyze and design detection and defense mechanisms against multiple types of attacks for CPSs requires new system frameworks. Besides security, other requirements such as optimal control cost also need to be considered. The hybrid game model we propose in this work contains physical states that are described by the system dynamics, and a cyber state that represents the detection mode of the system composed by a set of subsystems. A strategy means selecting a subsystem by combining one controller, one estimator and one detector among a finite set of candidate components at each state. Based on the game model, we propose a suboptimal value iteration algorithm for a finite horizon game, and prove that the algorithm results an upper bound for the value of the finite horizon game. A moving-horizon approach is also developed in order to provide a scalable and real-time computation of the switching strategies. Both algorithms aims at obtaining a saddle-point equilibrium policy for balancing the system's security overhead and control cost. The paper illustrates these concepts using numerical examples, and we compare the results with previously system designs that only equipped with one type of controller., Provionally accepted as a regular paper, Automatica, 11 pages
- Published
- 2017
24. Distributing Sequential Control for Manufacturing Automation Systems.
- Author
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Jakovljevic, Zivana, Lesi, Vuk, Mitrovic, Stefan, and Pajic, Miroslav
- Subjects
PETRI nets ,AUTOMATION ,MODULAR design ,MANUFACTURING process automation ,INTELLIGENT sensors ,ACTUATORS - Abstract
Recent trends in manufacturing require the use of reconfigurable equipment that facilitates rapid and cost-effective change of functionality through modular design, which supports fast integration. Intelligent devices (e.g., sensors, actuators) with integrated computation and communication capabilities enable high-level modularity, not only with the respect to hardware components but also in terms of control functionality; this can be achieved by distributing control to different network-connected devices. Thus, to enable fast and reliable system reconfigurations, in this brief, we introduce a method for distribution of control tasks and generation of control code for the devices in the control network. Our approach is based on the control interpreted Petri nets (CIPNs) formalism. We start from a CIPN capturing the centralized (overall) control system, and the mapping of input and output signals to local controllers (LCs) (i.e., smart devices) that have direct physical access to system sensors and actuators. From these, our method automatically designs distributed control tasks for LCs in the network, as well as generates control code for each LC. The applicability of the proposed method is experimentally verified on two real-world case studies. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
25. Relaxing Integrity Requirements for Attack-Resilient Cyber-Physical Systems.
- Author
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Jovanov, Ilija and Pajic, Miroslav
- Subjects
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CYBER physical systems , *DATA integrity , *INTEGRITY , *TECHNICAL specifications , *KALMAN filtering , *DETECTORS - Abstract
The increase in network connectivity has also resulted in several high-profile attacks on cyber-physical systems. An attacker that manages to access a local network could remotely affect control performance by tampering with sensor measurements delivered to the controller. Recent results have shown that with network-based attacks, such as man-in-the-middle attacks, the attacker can introduce an unbounded state estimation error if measurements from a suitable subset of sensors contain false data when delivered to the controller. While these attacks can be addressed with the standard cryptographic tools that ensure data integrity, their continuous use would introduce significant communication and computation overhead. Consequently, we study effects of intermittent data integrity guarantees on system performance under stealthy attacks. We consider linear estimators equipped with a general type of residual-based intrusion detectors (including, e.g., widely used $\chi ^2$ detectors) and show that even when integrity of sensor measurements is enforced only intermittently, the attack impact is significantly limited; specifically, the state estimation error is bounded or the attacker cannot remain stealthy. Furthermore, we present methods to: 1) evaluate the effects of any given integrity enforcement policy in terms of reachable state estimation errors for any type of stealthy attacks; and 2) design an enforcement policy that provides the desired estimation error guarantees under attack. Finally, on three automotive case studies, we show that even with less than 10% of authenticated messages, we can ensure satisfiable control performance in the presence of attacks. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
26. Statistical Verification of Hyperproperties for Cyber-Physical Systems.
- Author
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YU WANG, ZAREI, MOJTABA, BONAKDARPOUR, BORZOO, and PAJIC, MIROSLAV
- Subjects
CYBER physical systems ,STATISTICAL significance ,MARKOV processes ,UNCERTAIN systems ,MACHINE theory ,ROBOTIC path planning - Abstract
Many important properties of cyber-physical systems (CPS) are defined upon the relationship between multiple executions simultaneously in continuous time. Examples include probabilistic fairness and sensitivity to modeling errors (i.e., parameters changes) for real-valued signals. These requirements can only be specified by hyperproperties. In this article, we focus on verifying probabilistic hyperproperties for CPS. To cover a wide range of modeling formalisms, we first propose a general model of probabilistic uncertain systems (PUSs) that unify commonly studied CPS models such as continuous-time Markov chains (CTMCs) and probabilistically parametrized Hybrid I/O Automata (P²HIOA). To formally specify hyperproperties, we propose a new temporal logic, hyper probabilistic signal temporal logic (HyperPSTL) that serves as a hyper and probabilistic version of the conventional signal temporal logic (STL). Considering the complexity of real-world systems that can be captured as PUSs, we adopt a statistical model checking (SMC) approach for their verification. We develop a new SMC technique based on the direct computation of significance levels of statistical assertions for HyperPSTL specifications, which requires no a priori knowledge on the indifference margin. Then, we introduce SMC algorithms for HyperPSTL specifications on the joint probabilistic distribution of multiple paths, as well as specifications with nested probabilistic operators quantifying different paths, which cannot be handled by existing SMC algorithms. Finally, we show the effectiveness of our SMC algorithms on CPS benchmarks with varying levels of complexity, including the Toyota Powertrain Control System. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
27. Efficient and Adaptive Error Recovery in a Micro-Electrode-Dot-Array Digital Microfluidic Biochip.
- Author
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Li, Zipeng, Lai, Kelvin Yi-Tse, McCrone, John, Yu, Po-Hsien, Chakrabarty, Krishnendu, Pajic, Miroslav, Ho, Tsung-Yi, and Lee, Chen-Yi
- Subjects
MICROFLUIDICS ,BIOCHIPS ,MICROELECTRODES ,LINEAR programming ,INTEGERS - Abstract
A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. In recent years, DMFBs based on a micro-electrode-dot-array (MEDA) architecture have been proposed. MEDA biochips can provide advantages of better capability of droplet manipulation and real-time sensing ability. However, errors are likely to occur due to defects, chip degradation, and the lack of precision inherent in biochemical experiments. Therefore, an efficient error-recovery strategy is essential to ensure the correctness of assays executed on MEDA biochips. By exploiting MEDA-specific advances in droplet sensing, we present a novel error-recovery technique to dynamically reconfigure the biochip using real-time data provided by on-chip sensors. Local recovery strategies based on probabilistic-timed-automata are presented for various types of errors. An online synthesis technique and a control flow are also proposed to connect local-recovery procedures with global error recovery for the complete bioassay. Moreover, an integer linear programming-based method is also proposed to select the optimal local-recovery time for each operation. Laboratory experiments using a fabricated MEDA chip are used to characterize the outcomes of key droplet operations. The PRISM model checker and three benchmarks are used for an extensive set of simulations. Our results highlight the effectiveness of the proposed error-recovery strategy. [ABSTRACT FROM PUBLISHER]
- Published
- 2018
- Full Text
- View/download PDF
28. Making the Internet-of-Things a reality: From smart models, sensing and actuation to energy-efficient architectures.
- Author
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Bogdan, Paul, Pajic, Miroslav, Pande, Partha Pratim, and Raghunathan, Vijay
- Published
- 2016
29. A real-time digital-microfluidic platform for epigenetics.
- Author
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Ibrahim, Mohamed, Boswell, Craig, Chakrabarty, Krishnendu, Scott, Kristin, and Pajic, Miroslav
- Published
- 2016
- Full Text
- View/download PDF
30. Three challenges in cyber-physical systems.
- Author
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Mangharam, Rahul, Abbas, Houssam, Behl, Madhur, Jang, Kuk, Pajic, Miroslav, and Jiang, Zhihao
- Published
- 2016
- Full Text
- View/download PDF
31. Estimation of Blood Oxygen Content Using Context-Aware Filtering.
- Author
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Ivanov, Radoslav, Atanasov, Nikolay, Weimer, James, Pajic, Miroslav, Simpao, Allan, Rehman, Mohamed, Pappas, George, and Lee, Insup
- Published
- 2016
- Full Text
- View/download PDF
32. Scalable Verification of Linear Controller Software.
- Author
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Park, Junkil, Pajic, Miroslav, Lee, Insup, and Sokolsky, Oleg
- Published
- 2016
- Full Text
- View/download PDF
33. Security-Aware Scheduling of Embedded Control Tasks.
- Author
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LESI, VUK, JOVANOV, ILIJA, and PAJIC, MIROSLAV
- Subjects
EMBEDDED computer systems ,COMPUTER systems ,CYBER physical systems ,MIXED integer linear programming ,RESOURCE allocation - Abstract
In this work, we focus on securing cyber-physical systems (CPS) in the presence of network-based attacks, such as Man-in-the-Middle (MitM) attacks, where a stealthy attacker is able to compromise communication between system sensors and controllers. Standard methods for this type of attacks rely on the use of cryptographic mechanisms, such as Message Authentication Codes (MACs) to ensure data integrity. However, this approach incurs significant computation overhead, limiting its use in resource constrained systems. Consequently, we consider the problem of scheduling multiple control tasks on a shared processor while providing a suitable level of security guarantees. Specifically, by security guarantees we refer to control performance, i.e., Quality-of-Control (QoC), in the presence of attacks. We start by mapping requirements for QoC under attack into constraints for security-aware control tasks that, besides standard control operations, intermittently perform data authentication. This allows for the analysis of the impact that security-related computation overhead has on both schedulability of control tasks and QoC. Building on this analysis, we introduce a mixed-integer linear programming-based technique to obtain a schedulable task set with predefined QoC requirements. Also, to facilitate optimal resource allocation, we provide a method to analyze interplay between available computational resources and the overall QoC under attack, and show how to obtain a schedulable task set that maximizes the overall QoC guarantees. Finally, we prove usability of our approach on a case study with multiple automotive control components. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
34. Synthesis of Error-Recovery Protocols for Micro-Electrode-Dot-Array Digital Microfluidic Biochips.
- Author
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ELFAR, MAHMOUD, ZHANWEI ZHONG, ZIPENG LI, CHAKRABARTY, KRISHNENDU, and PAJIC, MIROSLAV
- Subjects
MICROFLUIDICS ,LABS on a chip ,MICROELECTRODES ,ELECTRODES ,BIOCHIPS - Abstract
A digital microfluidic biochip (DMFB) is an attractive technology platform for various biomedical applications. However, a conventional DMFB is limited by: (i) the number of electrical connections that can be practically realized, (ii) constraints on droplet size and volume, and (iii) the need for special fabrication processes and the associated reliability/yield concerns. To overcome the above challenges, DMFBs based on a microelectrode- dot-array (MEDA) architecture have been proposed and fabricated recently. Error recovery is of key interest for MEDA biochips due to the need for system reliability. Errors are likely to occur during droplet manipulation due to defects, chip degradation, and the uncertainty inherent in biochemical experiments. In this paper, we first formalize error-recovery objectives, and then synthesize optimal error-recovery protocols using a model based on Stochastic Multiplayer Games (SMGs). We also present a global error-recovery technique that can update the schedule of fluidic operations in an adaptive manner. Using three representative real-life bioassays, we show that the proposed approach can effectively reduce the bioassay completion time and increase the probability of success for error recovery. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
35. Design methodologies for securing cyber-physical systems.
- Author
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Faruque, Mohammad Al, Regazzoni, Francesco, and Pajic, Miroslav
- Published
- 2015
- Full Text
- View/download PDF
36. Automatic verification of linear controller software.
- Author
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Pajic, Miroslav, Park, Junkil, Lee, Insup, Pappas, George J., and Sokolsky, Oleg
- Published
- 2015
- Full Text
- View/download PDF
37. Robust estimation using context-aware filtering.
- Author
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Ivanov, Radoslav, Atanasov, Nikolay, Pajic, Miroslav, Pappas, George, and Lee, Insup
- Published
- 2015
- Full Text
- View/download PDF
38. Attack-resilient state estimation in the presence of noise.
- Author
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Pajic, Miroslav, Tabuada, Paulo, Lee, Insup, and Pappas, George J.
- Published
- 2015
- Full Text
- View/download PDF
39. Resilient multidimensional sensor fusion using measurement history.
- Author
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Ivanov, Radoslav, Pajic, Miroslav, and Lee, Insup
- Published
- 2014
- Full Text
- View/download PDF
40. Coding sensor outputs for injection attacks detection.
- Author
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Miao, Fei, Zhu, Quanyan, Pajic, Miroslav, and Pappas, George J.
- Published
- 2014
- Full Text
- View/download PDF
41. Opportunistic sensor scheduling in wireless control systems.
- Author
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Gatsis, Konstantinos, Pajic, Miroslav, Ribeiro, Alejandro, and Pappas, George J.
- Published
- 2014
- Full Text
- View/download PDF
42. Attack resilient state estimation for autonomous robotic systems.
- Author
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Bezzo, Nicola, Weimer, James, Pajic, Miroslav, Sokolsky, Oleg, Pappas, George J., and Lee, Insup
- Published
- 2014
- Full Text
- View/download PDF
43. Attack-resilient minimum mean-squared error estimation.
- Author
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Weimer, James, Bezzo, Nicola, Pajic, Miroslav, Sokolsky, Oleg, and Lee, Insup
- Published
- 2014
- Full Text
- View/download PDF
44. Robustness of attack-resilient state estimators.
- Author
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Pajic, Miroslav, Weimer, James, Bezzo, Nicola, Tabuada, Paulo, Sokolsky, Oleg, Lee, Insup, and Pappas, George J.
- Published
- 2014
- Full Text
- View/download PDF
45. Opportunistic scheduling of control tasks over shared wireless channels.
- Author
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Gatsis, Konstantinos, Pajic, Miroslav, Ribeiro, Alejandro, and Pappas, George J.
- Published
- 2014
- Full Text
- View/download PDF
46. Attack-resilient sensor fusion.
- Author
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Ivanov, Radoslav, Pajic, Miroslav, and Lee, Insup
- Published
- 2014
- Full Text
- View/download PDF
47. Design and Implementation of Attack-Resilient Cyberphysical Systems: With a Focus on Attack-Resilient State Estimators.
- Author
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Pajic, Miroslav, Weimer, James, Bezzo, Nicola, Sokolsky, Oleg, Pappas, George J., and Lee, Insup
- Subjects
SUPERVISORY control systems ,STUXNET (Computer worm) ,CYBER physical systems ,CYBERTERRORISM ,COUNTERTERRORISM ,STEEL mills - Abstract
Recent years have witnessed a significant increase in the number of securityrelated incidents in control systems. These include high-profile attacks in a wide range of application domains, from attacks on critical infrastructure, as in the case of the Maroochy Water breach [1], and industrial systems (such as the StuxNet virus attack on an industrial supervisory control and data acquisition system [2], [3] and the German Steel Mill cyberattack [4], [5]), to attacks on modern vehicles [6]-[8]. Even high-assurance military systems were shown to be vulnerable to attacks, as illustrated in the highly publicized downing of the RQ-170 Sentinel U.S. drone [9]-[11]. These incidents have greatly raised awareness of the need for security in cyberphysical systems (CPSs), which feature tight coupling of computation and communication substrates with sensing and actuation components. However, the complexity and heterogeneity of this next generation of safety-critical, networked, and embedded control systems have challenged the existing design methods in which security is usually consider as an afterthought. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
48. Recognition of Planar Segments in Point Cloud Based on Wavelet Transform.
- Author
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Jakovljevic, Zivana, Puzovic, Radovan, and Pajic, Miroslav
- Abstract
Within industrial automation systems, three-dimensional (3-D) vision provides very useful feedback information in autonomous operation of various manufacturing equipment (e.g., industrial robots, material handling devices, assembly systems, and machine tools). The hardware performance in contemporary 3-D scanning devices is suitable for online utilization. However, the bottleneck is the lack of real-time algorithms for recognition of geometric primitives (e.g., planes and natural quadrics) from a scanned point cloud. One of the most important and the most frequent geometric primitive in various engineering tasks is plane. In this paper, we propose a new fast one-pass algorithm for recognition (segmentation and fitting) of planar segments from a point cloud. To effectively segment planar regions, we exploit the orthonormality of certain wavelets to polynomial function, as well as their sensitivity to abrupt changes. After segmentation of planar regions, we estimate the parameters of corresponding planes using standard fitting procedures. For point cloud structuring, a z-buffer algorithm with mesh triangles representation in barycentric coordinates is employed. The proposed recognition method is tested and experimentally validated in several real-world case studies. [ABSTRACT FROM PUBLISHER]
- Published
- 2015
- Full Text
- View/download PDF
49. Diagnosis of irregularities in the robotized part mating process based on contextual recognition of contact states transitions.
- Author
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Jakovljevic, Zivana, Petrovic, Petar B., Milkovic, Dragan, and Pajic, Miroslav
- Subjects
AUTOMATION ,MANUFACTURING processes ,ARTIFICIAL intelligence ,COMPLIANT mechanisms ,MACHINE parts ,ROBOT control systems - Abstract
Purpose – The purpose of this paper is to provide a method for the generation of information machines for part mating process diagnosis. Recognition of contact states between parts during robotized part mating represents a significant element of the system for active compliant robot motion. All proposed information machines for contact states recognition will recognize one of the possible contact states even when irregular events in the process occur, and the active motion planner will continue to send commands to robot controller according to the planned trajectory. Design/methodology/approach – The presented framework is based on the general theory of automata and formal languages. Starting from possible regular contact states transitions in part mating, the authors create an automaton for diagnostics, which, besides regular, accepts all irregular (observable and unobservable) process sequences. Findings – Contact states do not appear arbitrarily during regular processes, but in certain context. Theory of automata represents a solid basis for contextual recognition and diagnosis of irregularities in part mating. Research limitations/implications – The proposed methodology is elaborated and experimentally verified using an example of cylindrical part mating, and stick-slip effect as an observable irregularity. The future work will address the generation of diagnosers for other types of part mating tasks and extension of the set of observable irregularities. Practical implications – The process diagnosis increases the robustness of active compliant motion system. Originality/value – Although very important feedback information provider for active motion planner, part mating process monitoring was not frequently addressed in the past. In this paper, the authors propose a methodology for generation of part mating process diagnoser that is based on general automata theory. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF
50. Stabilizability over deterministic relay networks.
- Author
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Pajic, Miroslav, Sundaram, Shreyas, and Pappas, George J.
- Published
- 2013
- Full Text
- View/download PDF
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