Article
Automation & Control Systems
Moumita Mukherjee, Avijit Banerjee, Sumeet Gajanan Satpute, George Nikolakopoulos
Summary: A decentralized multi-sensor fusion-based resilient pose estimation architecture is proposed for autonomous navigation of satellites around an asteroid. The framework incorporates automatic fault detection and isolation, as well as fault-resilient optimal information filter fusion techniques. Simulation studies demonstrate the effectiveness and superiority of the proposed approach.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Ruiyuan Wu, Wing-Kin Ma, Yuening Li, Anthony Man-Cho So, Nicholas D. Sidiropoulos
Summary: This study presents PRISM, a probabilistic simplex component analysis approach to identifying the vertices of a data-circumscribing simplex from data. PRISM uses a simple probabilistic model and carries out inference by maximum likelihood. It has strong connections with simplex volume minimization and shows potential in combating noise.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Biochemical Research Methods
Ariel A. Hippen, Matias M. Falco, Lukas M. Weber, Erdogan Pekcan Erkan, Kaiyang Zhang, Jennifer Anne Doherty, Anna Vaharautio, Casey S. Greene, Stephanie C. Hicks
Summary: The miQC package was developed to predict low-quality cells in a given scRNA-seq dataset by jointly modeling the proportion of reads mapping to mitochondrial DNA (mtDNA) genes and the number of detected genes using mixture models in a probabilistic framework. The QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells for downstream analyses.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Zheng Zhao, Simo Sarkka, Jens Sjolund, Thomas B. Schon
Summary: We propose a continuous-time probabilistic approach to estimate the chirp signal and its instantaneous frequency function in the absence of true forms. Our model employs non-linear cascaded Gaussian processes represented as non-linear stochastic differential equations. The posterior distribution of the functions is estimated using stochastic filters and smoothers. We derive a (posterior) Cramer-Rao lower bound and theoretical upper bound for the estimation error. Experimental results demonstrate that our method outperforms state-of-the-art methods on synthetic data and works effectively on real-world datasets.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
David Hong, Kyle Gilman, Laura Balzano, Jeffrey A. Fessler
Summary: This paper introduces a new variant of probabilistic PCA, HePPCAT, which is able to better handle the common issue of heterogeneous data in modern applications. By incorporating heteroscedasticity into the statistical model and using efficient alternating maximization algorithms, this method achieves superior performance compared to traditional PCA methods.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Houping Xiao, Shiyu Wang
Summary: This paper proposes a unified truth discovery algorithm, which uses maximum likelihood estimation to estimate source reliability and truth values. It proves the consistency of the estimation and the convergence of the algorithm, and conducts experiments to support the theoretical results.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Agriculture, Multidisciplinary
Piyanun Ruangurai, Matthew N. Dailey, Mongkol Ekpanyapong, Peeyush Soni
Summary: With the development of precision agriculture technology, machine vision is being used to obtain accurate spatial information for control systems in a cost-effective manner. In the research reported here, a machine vision-based guidance system for a seeding tractor was developed and tested for rice planting in wet and puddled paddy fields. The system utilized the furrow/rut pattern created by the tractor's wheels as input for steering and velocity control. The results showed that using PCA as an initial estimate followed by iterative optimization of a new likelihood function achieved the best navigation accuracy.
PRECISION AGRICULTURE
(2022)
Article
Robotics
Junhyoung Ha
Summary: In this study, a probabilistic framework is proposed for hand-eye and robot-world calibration. The framework clarifies the assumptions of existing methods and provides optimal coordination of transformations for distance minimization. An iterative algorithm is proposed to account for different noise properties of individual measurements, and an estimation uncertainty analysis is presented to quantify the expected estimation accuracy.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Engineering, Electrical & Electronic
Sebastian Semper, Michael Doebereiner, Christian Steinmetz, Markus Landmann, Reiner S. Thomae
Summary: Multidimensional channel sounding is used to measure the geometrical structure of mobile radio propagation by estimating the parameters of a multipath data model. The estimation is done using observations in frequency, time, and space, and the maximum likelihood estimation framework allows for high resolution in all dimensions. An appropriate parametric data model is necessary to accurately represent the multipath propagation, as well as a device data model that comes from calibration measurements. The extension of the multidimensional Richter maximization approach (RIMAX) parameter estimation framework with proper frequency responses shows better performance for higher relative bandwidths compared to conventional RIMAX implementation.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2023)
Article
Chemistry, Analytical
Moumita Mukherjee, Avijit Banerjee, Andreas Papadimitriou, Sina Sharif Mansouri, George Nikolakopoulos
Summary: This article proposes a novel decentralized two-layered and multi-sensorial based fusion architecture for establishing a novel resilient pose estimation scheme. The first layer integrates pose information from different sensors, while the second layer introduces a Fault Resilient Optimal Information Fusion paradigm to provide trusted pose estimation. The architecture enables self-resiliency through a built-in fault isolation mechanism and can address sensor failures or erroneous measurements.
Article
Multidisciplinary Sciences
Ye Lin, Sean B. Andersson
Summary: Single Particle Tracking (SPT) is a well-known tool for studying the dynamics of biological macromolecules inside living cells. The study focuses on the problem of localization and parameter estimation and proposes an Expectation Maximization (EM) based framework for simultaneous handling. Two representative methods, namely SMC-EM and U-EM, demonstrate better performance compared to standard techniques, especially at low signal levels.
Article
Automation & Control Systems
Yanling Chang, Alfredo Garcia, Zhide Wang, Lu Sun
Summary: This article discusses the (inverse) structural estimation of POMDPs based on observable sequences and implemented actions. The structural properties of an entropy regularized POMDP are analyzed, and conditions for model identifiability without knowledge of state dynamics are specified. A soft policy gradient algorithm is used to compute a maximum likelihood estimator, and an equipment replacement problem is used as an illustration.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Biochemical Research Methods
Mohammadreza Mohaghegh Neyshabouri, Jens Lagergren
Summary: Identifying the interrelations among cancer driver genes and the patterns in which they get mutated is critical for understanding cancer. In this paper, the authors propose a method for analyzing cohorts of tumors to identify the specific process in which driver genes accumulate critical mutations. They introduce a tree model to represent the mutation accumulation process and develop a computationally efficient dynamic programming procedure and Markov Chain Monte Carlo inference algorithm for analyzing large datasets. The authors demonstrate the effectiveness of their method through synthetic and biological dataset analyses, providing new insights into the relation among driver genes.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Pei-Duo Yu, Chee Wei Tan, Hung-Lin Fu
Summary: This paper studies the epidemic source detection problem in contact tracing networks using the susceptible-infected model in epidemiology. By analyzing finite degree regular graphs and regular graphs with cycles, the mathematical equivalence between acyclic and cyclic graphs is established. A novel statistical distance centrality is proposed to refine the solution of the maximum likelihood estimator. The performance evaluation shows that the proposed algorithm outperforms existing heuristics in correctly identifying superspreaders in real infection clusters.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
YunPeng Li, ZhaoHui Ye
Summary: This letter introduces a novel boosting-based method for univariate nonparametric estimation, deducing the boosting algorithm through second-order approximation of nonparametric log-likelihood, and choosing Gaussian kernel and smooth spline as weak learners to satisfy the smoothing assumptions. Simulations and real data experiments demonstrate the efficacy of the proposed approach.
IEEE SIGNAL PROCESSING LETTERS
(2021)
Article
Automation & Control Systems
Vasileios Tzoumas, Luca Carlone, George J. Pappas, Ali Jadbabaie
Summary: The study focuses on the joint design of sensing and control policies, tackling two dual problem instances: sensing-constrained LQG control and minimum-sensing LQG control. While no polynomial time algorithm guarantees a constant approximation factor from the optimal across all problem instances, the authors present the first polynomial time algorithms with per-instance suboptimality guarantees. The research frames LQG codesign as the optimization of approximately supermodular set functions, developing novel algorithms and establishing connections between suboptimality and control-theoretic quantities.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Correction
Robotics
Matteo Palieri, Benjamin Morrell, Abhishek Thakur, Kamak Ebadi, Jeremy Nash, Arghya Chatterjee, Christoforos Kanellakis, Luca Carlone, Cataldo Guaragnella, Ali-akbar Agha-mohammadi
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Matteo Palieri, Benjamin Morrell, Abhishek Thakur, Kamak Ebadi, Jeremy Nash, Arghya Chatterjee, Christoforos Kanellakis, Luca Carlone, Cataldo Guaragnella, Ali-akbar Agha-mohammadi
Summary: A high-precision lidar odometry system, named LOCUS, is proposed in this work to achieve robust and real-time operation under challenging perceptual conditions, incorporating a multi-stage scan matching unit and a sensor integration module for seamless fusion.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Automation & Control Systems
Vasileios Tzoumas, Ali Jadbabaie, George J. Pappas
Summary: In this article, the authors propose a robust and adaptive maximization algorithm for solving discrete optimization problems in adversarial environments. The algorithm, called RAM, runs in an online fashion and adapts to the history of failures in each step. It guarantees near-optimal performance and has both provable per-instance a priori bounds and tight and/or optimal a posteriori bounds.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Robotics
Brent Schlotfeldt, Vasileios Tzoumas, George J. Pappas
Summary: This article introduces a robust and adaptive multirobot planning algorithm RAIN, which can plan information acquisition tasks in adversarial environments and exhibits superior performance in multiple information acquisition scenarios.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Robotics
Yulun Tian, Yun Chang, Fernando Herrera Arias, Carlos Nieto-Granda, Jonathan P. How, Luca Carlone
Summary: This paper presents $\mathsf {\text{Kimera-Multi}}$, a multi-robot SLAM system that is robust, fully distributed, and capable of capturing semantic information. Experimental results demonstrate its superior performance.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Robotics
Lifeng Zhou, Vasileios Tzoumas, George J. Pappas, Pratap Tokekar
Summary: In this article, algorithms are designed to protect swarm-robotics applications against sensor denial-of-service attacks, and a distributed robust maximization algorithm is proposed. The distributed approach improves computational speed and achieves tracking performance comparable to centralized algorithms in simulations. Additionally, an improved distributed robust maximization algorithm is introduced to infer attack quantities more accurately.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Robotics
Andrzej Reinke, Matteo Palieri, Benjamin Morrell, Yun Chang, Kamak Ebadi, Luca Carlone, Ali-Akbar Agha-Mohammadi
Summary: This research presents LOCUS 2.0, a robust and computationally-efficient lidar odometry system for real-time underground 3D mapping. LOCUS 2.0 includes a novel normals-based GICP formulation, an adaptive voxel grid filter, and a sliding-window map approach to reduce computation time and memory consumption. The proposed approach is suitable for use on heterogeneous robotic platforms in large-scale environments with severe computation and memory constraints.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Christopher E. Denniston, Yun Chang, Andrzej Reinke, Kamak Ebadi, Gaurav S. Sukhatme, Luca Carlone, Benjamin Morrell, Ali-akbar Agha-mohammadi
Summary: This study describes a loop closure module that optimizes the computation of loop closures to maintain a drift-free centralized map. Experimental results demonstrate that the system can generate and maintain a map with low error, and effectively select loop closures.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Zirui Xu, Hongyu Zhou, Vasileios Tzoumas
Summary: We introduce a submodular coordination algorithm with bounded tracking regret to enable multiple robots to coordinate in dynamic, unstructured, and adversarial environments for tasks such as target tracking, environmental mapping, and area monitoring.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Engineering, Multidisciplinary
Luca Ballotta, Luca Schenato, Luca Carlone
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2020)