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With the rapid development of information technologies, the computing, networking, and physical elements in industrial environments are becoming tightly amalgamated with each other, resulting in the formation of the so-called Industrial Cyber-Physical Systems (ICPS). These systems forge the core of current real-world networked industrial infrastructures, having a cyber-representation of physical assets

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This special issue of the IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (T-ASE) focuses on how the state-of-the-art achievements and applications in the general area of artificial intelligence in automation for autonomous unmanned systems applications. As Guest Editors, we are very pleased to present the selected 16 articles, whose topics are specifically related to artificial intelligence

The IEEE Transactions on Automation Science and Engineering (T-ASE) wishes to thank the 1649 reviewers over the past year who have performed an essential role in maintaining the quality of this publication. T-ASE strives for the 90–90 standard, i.e., 90% of articles should be reviewed within 90 days of submission. The review process starts when the Editor-in-Chief assigns the paper to an Editor, who

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Artificial intelligence-based cyber-physical systems (CPS) applications have been spread across various fields such as smart cities, medical services, and industrial controls. When CPS devices are connected to a cloud server, big data streams generated by CPS devices impose enormous bandwidth pressure and exert excessive compute loads to the cloud server. Due to unpredictable environments and uncertainty

The operation time of an ideal reliable wafer scanner model is defined at the die level where the actual exposure process takes place as the time unit per die, or at the wafer substrate level as the time unit per wafer substrate. Therefore, the machine throughput is given as the reciprocal of the operation time. The involved motion profiles of a machine, namely the step-and-scan trajectories, function

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We are pleased to present this Special Issue of TASE, including 12 extended articles selected from the technical program of the 2020 International Conference on Automation Science and Engineering (CASE2020). CASE2020 was held virtually due to the COVID19 pandemics, August 20–21, 2020, and was originally scheduled in Hong Kong, China. CASE is an offspring of TASE and is the flagship automation conference

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Most traditional industries or emerging countries may not be capable of directly transiting to Industry 4.0. To fill the gap between as-is Industry 3.0 and to-be Industry 4.0, some disruptive innovations from automation and industrial engineering identify best practice with adopting cost-effective semi-automated systems to manage the potential socio-economic impacts of infrastructure disruptions, while

This IEEE Transactions on Automation Science and Engineering (T-ASE) Special Section on New Frontiers in Smart Factories: Smart Automation and Human–Robot Interaction focuses on promising, innovative research outcomes and industrial applications of different key technologies for smart automation and human–robot interaction.

Dr. Philippe Lutz mymargin passed mymargin away on May 14, 2022, due to a sudden cardiac arrest. He was a passionate researcher, a devoted teacher, and a committed leader. He was caring and extremely supportive to colleagues. We lost a great colleague and friend whom we will miss with pain and sadness. Dr. Lutz joined the University of Franche-Comté, Besancon, as a Professor, in 2002. He was the Head

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This work presents a Multiple Depot Traveling Salesman Problem with revisit period constraints. The revisit period constraints are relevant to persistent routing applications, where these constraints represent maximum time between successive visits to a target. This problem is first posed as a Mixed Integer Linear Program. The coupling constraints in the primal problem are then relaxed via Lagrangian

We study the problem of allocating a set of indivisible operations to a set of agents in a fair and efficient manner while also minimizing the makespan. We first present the Operation Trading Algorithm that generates allocations satisfying the DEQx (Duplicated Equitability up to any operation) fairness criterion while also guaranteeing an upper bound of 2 on the makespan for identical agents. The pairwise

In manufacturing, machine selection and buffer allocation are extremely important and widely studied problems, as both can significantly affect the system performance. Solving either problem alone in a deterministic setting is already challenging. In this study, however, we simultaneously solve a high dimensional machine selection and buffer allocation problem in a highly stochastic and complex production

In this paper, we address the problem of automating the definition of feasible pallets configurations. This issue is crucial for the competitiveness of logistic companies and is still one of the most difficult problems in internal logistics. In fact, it requires the fast solution of a three-dimensional Bin Packing Problem (3D-BPP) with additional logistic specifications that are fundamental in real

Deep drawing is a metalworking procedure aimed at getting a cold metal sheet plastically deformed in accordance with a pre-defined mould. Although this procedure is well-established in industry, it is still susceptible to several issues affecting the quality of the stamped metal products. In order to reduce defects of workpieces, process control approaches can be performed. Typically, process control

Cascading failure models are important for understanding the mechanism of blackouts and evaluating the control strategies to prevent the failure propagation. The evolution of cascading failure in actual power grid is a continuous dynamic process triggered by discrete events, such as initial disturbances and physical responses. In this paper, we develop an event-triggered hybrid system model to describe

While job scheduling problems have been studied extensively, scheduling problems with endogenous yield rates that may be affected by predictive maintenance is not thoroughly investigated. In this study, we consider the optimization of a joint predictive maintenance and job scheduling problem for the minimization of total shortage penalty. As maintenance may be conducted to raise machine yield rates

The Conflict-Free Electric Vehicle Routing Problem (CF-EVRP) is an extension of the Vehicle Routing Problem (VRP), a combinatorial optimization problem of designing routes for vehicles to visit customers such that a cost function, typically the number of vehicles or the total travelled distance, is minimized. The problem finds many logistics applications, particularly for highly automated logistic

A precise localization system and a map that properly represents the environment are fundamental for several robotic applications. Traditional LiDAR SLAM algorithms are particularly susceptible to underestimating the distance covered by real robots in environments with few geometric features. Common industrial confined spaces, such as ducts and galleries, have long and homogeneous structures, which

The COVID-19 pandemic shows growing demand of robots to replace humans for conducting multiple tasks including logistics, patient care, and disinfection in contaminated areas. In this paper, a new autonomous disinfection robot is proposed based on aerosolized hydrogen peroxide disinfection method. Its unique feature lies in that the autonomous navigation is planned by developing an atomization disinfection

In this paper, we revisit state estimation and weak detectability verification for discrete event systems (DES) from a span-new perspective. Specifically, using the semi-tensor product (STP) technique, we construct two new matrix-based information structures called a current-state estimator (C-estimator) and an initial-state estimator (I-estimator) for computing three fundamental types of state estimates

In this paper, we propose spatiotemporal co-attention hybrid neural network (SC-HNN), a novel hybrid neural network model with both spatial and temporal attention mechanisms for pose-invariant inertial odometry. The main idea is to extract both local and global features from a window of IMU measurements for velocity prediction. SC-HNN leverages the convolutional neural network (CNN) to capture the

Swarm foraging is a common test case application for multi-robot systems. In this paper RepAtt algorithm is used for improving coordination of a robot swarm by selectively broadcasting repulsion and attraction signals. This is a chemotaxis-inspired search behaviour where robots use the temporal gradients of these signals to navigate towards more advantageous areas. Hardware experiments were used to

Effective scheduling for byproduct gas systems of steel industry is becoming increasingly vital for maintaining their safe operating and improving energy utilization. Considering that the existing studies failed to capture the dynamic changes in the production environment, a novel dynamic scheduling framework is proposed that seamingly integrates expert knowledge with a dynamic programming process

Emergency departments (EDs) are facing increasing overcrowding and long patient waiting time, which is mainly caused by the time-varying demand of new and returning patients. In this paper, we focus on scheduling ED physicians to reduce the patient waiting time and the physician working hours. We consider the ED network as a time-varying queuing system with returns and provide an analytical methodology

In a Wireless Sensor Networks (WSN) based fluid pipeline leak monitoring system, numerous sensors are deployed along the pipeline networks. A great amount of measurements are continuously transmitted from the sensor nodes to their corresponding sink nodes. The energy consumed on data transmission dominates the power depletion of a WSN system. To reduce the amount of data transmission and prolong the

This paper proposes an iterative approach to separate a set of admissible markings of a nonlinear constraint into a number of subsets. At each iteration, we find a maximal subset of admissible markings that are separated from inadmissible markings by linear constraints. Then, the union of all the obtained subsets constitutes the set of all admissible markings. For each subset of admissible markings

Deadlock avoidance of flexible manufacturing systems (FMSs) has received increasing attention from both academic and industrial communities. There have been a large number of different types of deadlock avoidance policies discussed in the literature. However, how to avoid deadlocks in an efficient way is still one of the major obstacles, especially for large systems. In this paper, we propose a new

Due to the increasing adoption of smart sensing and Internet of things (IoT) devices, wind energy system (WES) becomes more vulnerable to cyber and physical attacks. Therefore, designing a secure and resilient WES is critical. This paper first proposes a system-of-systems (SoS) framework for the cyber-physical WES. Specifically, on the one hand, we adopt a game-theoretic model to capture the interactions

In this paper, an image-based impedance control strategy for force tracking of an unmanned aerial manipulator (UAM) is presented. Firstly, image features with nice decoupling characteristics are designed and the relationship between the camera motion and the image features is derived. Then, a two-stage strategy is proposed to achieve force tracking of the UAM on a planar object in an arbitrary pose

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The COVID-19 pandemic has not only posed a significant threat to health, life, economy, and the whole society but also led to numerous new theoretical and practical challenges for automation science and engineering. The goal of this Special Issue is to bring together researchers and practitioners into a forum to show the state-of-the-art research and applications in responding to the challenges and

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Background/foreground separation is one of the most fundamental tasks in computer vision, especially for video data. Robust PCA (RPCA) and its tensor extension, namely, Robust Tensor PCA (RTPCA), provide an effective framework for background/foreground separation by decomposing the data into low-rank and sparse components, which contain the background and the foreground (moving objects), respectively

This article aims to investigate the security consensus and composite anti-disturbance problems for a class of nonlinear multi-agent systems subjected to stochastic false data injection attacks (FDIAs) and multiple disturbances under a directed communication topology. To attenuate and reject of the negative effects of two types of disturbances, a disturbance observer (DO) is designed to counteract

In this paper, using the ball and beam system as an illustration, a control scheme is developed on human-robot collaboration, i.e., a two-level hierarchical framework is proposed to establish a robust human-robot collaboration (HRC) policy. On the high level, a deep reinforcement learning (DRL) algorithm is presented to plan the desired beam rotational velocity. The low level is constructed by a human-intention

Accurate objective, automated limb lameness detection and pose estimation play an important role for animal well-being and precision livestock farming. We present a wearable sensor-based limb lameness detection and pose estimation for horse walk and trot locomotion. The gait event and lameness detection are first built on a recurrent neural network (RNN) with long short-term memory (LSTM) cells. Its

Inspired by sequential additive manufacturing operations, we consider prediction tasks arising in processes that comprise of sequential sub-operations and propose a multi-stage inference procedure that exploits prior knowledge of the operational sequence. Our approach decomposes a data-driven model into several easier problems each corresponding to a sub-operation and then introduces a Bayesian inference

Laser metal deposition (LMD) is an additive manufacturing method for metal parts by using focused thermal energy to fuse materials as they are deposited. During LMD, transient thermal signatures such as the in-situ thermal images of melt pool, contain rich information about process performance. Early prediction of such transient thermal signatures provides opportunities for process monitoring and defect

Human-robot collaboration (HRC), where humans and robots work together to handle specific tasks, requires designing robots that can effectively support human beings. Robots need to conduct reasoning using commonsense knowledge (CSK), e.g., fundamental knowledge that humans possess and use subconsciously, in order to assist humans in challenging and dynamic environments. Currently, there are several

This paper presents a fast global collision detection method for robotic machining of large complex components, aiming to quickly determine whether there is a collision between the robot and the surrounding environment during the whole machining process. Geometric analysis shows that there are always some trajectory points on the motion path of the manipulator that are more likely to collide than the

Registration is highly demanded in many real-world scenarios such as robotics and automation. Registration is challenging partly due to the fact that the acquired data is usually noisy and has many outliers. In addition, in many practical applications, one point set (PS) usually only covers a partial region of the other PS. Thus, most existing registration algorithms cannot guarantee theoretical convergence