This Workshop on the Algorithmic Foundations of Robotics (WAFR) Special Issue of the IEEE Transactions on Automation Science and Engineering (T-ASE) brings together eight extended articles from the thirteenth WAFR. While these eight articles span several application domains, they demonstrate advances in automation through algorithmic development and analysis. Nomination to this Special Issue was done

This article presents a design for interlocking blocks and an algorithm that allows these blocks to be assembled into desired shapes. During and after assembly, the structure is kinematically interlocked if a small number of blocks are immobilized relative to other blocks. There are two types of blocks: cubes and double-height posts, each with a particular set of male and female joints. Layouts for

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To Perform reliably and consistently over sustained periods of time, large-scale automation critically relies on computer simulation. Simulation allows us and supervisory AI to effectively design, validate, and continuously improve complex processes, and helps practitioners to gain insight into the operation and justify future investments. While numerous successful applications of simulation in industry

Advancement in healthcare solutions is one of the major success stories of our times. While biomedical science and engineering has progressed significantly, increased human longevity has created huge demands on the healthcare system, such as the workforce that is struggling to meet the needs of patients. With the advent of healthcare automation, doctor offices, hospitals, and other medical facilities

Learning from subject’s calibration data can significantly improve the performance of a steady-state visually evoked potential (SSVEP)-based brain–computer interface (BCI), for example, the state-of-the-art target recognition methods utilize the learned subject-specific and stimulus-specific model parameters. Unfortunately, when dealing with new stimuli or new subjects, new calibration data must be

Energy places an important role in a new scale of urbanization, digitization, and industrialization. Going “energy-efficient” then becomes a major component of the missions for manufacturers and service providers to stay globally competitive. In recent years, the newly emerging intelligent technologies are enhancing the production process and control management in an energy-effective and -efficient

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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Consider a sensor that reports whether or not an event has occurred somewhere along a path, but that has no conception of where along the path that event has occurred. We name this type of sensor a path-based sensor and describe the recursive Bayesian update that can be used to calculate posterior beliefs about the presence of a sensor triggering phenomenon given a path-based sensor observation. We

Generating robot motion for multiple tasks in dynamic environments is challenging, requiring an algorithm to respond reactively while accounting for complex nonlinear relationships between tasks. In this article, we develop a novel policy synthesis algorithm, Riemannian motion policy (RMP)flow, based on geometrically consistent transformations of RMPs. RMPs are a class of reactive motion policies that

We examine a scheduling problem for a dual-armed cluster tool that processes multiple similar wafer types concurrently. It has been recently proved that the well-known swap sequence, which is widely used for single wafer type processing, also minimizes the cycle time for concurrent processing. In this article, we wish to minimize wafer delays in a process chamber, which are critical to wafer quality

The framework of partially observable Markov decision processes (POMDPs) offers a standard approach to model uncertainty in many robot tasks. Traditionally, POMDPs are formulated with optimality objectives. In this article, we study a different formulation of POMDPs with Boolean objectives . For robotic domains that require a correctness guarantee of accomplishing tasks, Boolean objectives are natural

Rearranging objects on a planar surface arises in a variety of robotic applications, such as product packaging. Using two arms can improve efficiency but introduces new computational challenges. This article studies the problem structure of object rearrangement using two arms in synchronous, monotone tabletop setups and develops an optimal mixed-integer model. It then describes an efficient and scalable

This article examines the selection of a robot’s actuation and sensing hardware to minimize the cost of that design while ensuring that the robot is capable of carrying out a plan to complete a task. Its primary contribution is in the study of the hardness of reasonable formal models for that minimization problem. Specifically, for the case in which sensing hardware is held fixed, we show that this

The hand gesture recognition system is a noncontact and intuitive communication approach, which, in turn, allows for natural and efficient interaction. This work focuses on developing a novel and robust gesture recognition system, which is insensitive to environmental illumination and background variation. In the field of gesture recognition, standard vision sensors, such as CMOS cameras, are widely

Smart manufacturing is targeted as the next generation of manufacturing by many national and international strategic development. The increasingly rich production data, the integration and extensive application of information technology, and the intelligent data processing and system modeling methods have collectively enabled smart manufacturing. Building upon them, manufacturing system modeling, knowledge

The 15th annual IEEE International Conference on Automation Science and Engineering (CASE 2019) was held on August 22–26, 2019, at The University of British Columbia, Vancouver, BC, Canada. IEEE CASE represents the flagship automation conference of the IEEE Robotics and Automation Society and constitutes the primary forum for cross-industry and multidisciplinary research in automation. Its goal is

Home care (HC) services represent an effective solution to face the health issues related to population aging. However, several scheduling problems arise in HC, and the providers must make several scheduling and routing decisions, e.g., the assignment of caregivers to clients, in order to balance operating costs and client satisfaction. Starting from the analysis of a real HC provider operating in

Tool-center-point (TCP) control increases the operating comfort of concrete pumps by shifting the control to the task space. The operation is accompanied by various requirements and constraints from the mechanical structure, the hydraulic system, and the operator. They must be taken into account for the efficient and error-free operation of the concrete pump. In this publication, a TCP control algorithm

Learning manipulation skills from open surgery provides more flexible access to the organ targets in the abdomen cavity and this could make the surgical robot working in a highly intelligent and friendly manner. Teaching by demonstration (TbD) is capable of transferring the manipulation skills from human to humanoid robots by employing active learning of multiple demonstrated tasks. This work aims

This article develops KL-ergodic exploration from equilibrium (KL-E 3 ), a method for robotic systems to integrate stability into actively generating informative measurements through ergodic exploration. Ergodic exploration enables robotic systems to indirectly sample from informative spatial distributions globally, avoiding local optima, and without the need to evaluate the derivatives of the distribution

Energy-efficient machining has become imperative for energy conservation, emission reduction, and cost saving of manufacturing sectors. Optimal machining parameter decision is regarded as an effective way to achieve energy efficient turning. For flexible machining, it is of utmost importance to determine the optimal parameters adaptive to various machines, workpieces, and tools. However, very little

Machine state control is one of the most promising energy-efficient measures for machining processes. A proper control reduces the energy consumed during idle periods by switching off/on the machines. A critical barrier for practical implementation is related to the knowledge of part arrival process that is affected by uncertainty. The stochastic processes involved in the system are usually assumed

In nature, biological organisms jointly evolve both their morphology and their neurological capabilities to improve their chances for survival. Consequently, task information is encoded in both their brains and their bodies. In robotics, the development of complex control and planning algorithms often bears sole responsibility for improving task performance. This dependence on centralized control can

Estimation of distribution algorithm (EDA) is an efficient population-based stochastic search technique. Since it was proposed, many attempts have been made to improve its performance in the context of nonlinear continuous optimization. However, the success of EDA depends on the accuracy of modeling, the effectiveness of sampling, and the ability of exploration. An effective EDA often needs to take

In recent years, lower limb exoskeletons have gained considerable interest in applications of walking assistance for paraplegic patients. In daily lives, the exoskeleton should have the ability to help the patients to walk over different terrains. For sloped terrains, how to plan the stepping locations on slopes with different gradients and generate stable human-like gaits for patients is a critical

Compliant, nonrigid parts are widely used in many industries today. Existing variation simulation analysis on the manufacturing part focuses on orientation and position deviation with part shape errors being largely omitted. This is a valid approach for the rigid part, but it is unrealistic and can be problematic for the compliant part. In this study, a new methodology has been introduced to compliant

A little volume of lower extremity amputees needs hip disarticulation prostheses (HDPs). This situation makes it hard to invite hip amputees for prostheses test. The traditional evaluations for HDPs mostly refer to the questionnaires from the amputees and lack of quantitative criteria. In this article, we proposed a gait simulation and evaluation (GSE) system for HDPs testing. The GSE system contained

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In recent decades, there has been an increasing interest in the use of robotic powered exoskeletons to assist patients with movement disorders in rehabilitation and daily life. Providing assistive torque that compensates for the user’s remaining muscle contributions is a growing and challenging field within exoskeleton control. In this article, ankle joint torques were estimated using electromyography

This article deals with reconfigurable uniprocessor systems powered by a renewable energy source under real-time and resource sharing constraints. A reconfigurable system is defined as a set of implementations, each of which is encoded by real-time periodic software tasks. Reconfiguration is a flexible runtime scenario that adapts the current system’s implementation to any related environment evolution

Gesture recognition becomes a thriving research area in modern human motion recognition systems. The intensification of demands on efficient interactive human–machine-interface systems, commercial objectives, and many other factors contributes to fuel this revival dynamics. Understanding human gestures becomes essential for prevention and health monitoring applications. In particular, analyzing hand

Understanding the effects of different hip assistance modes is a fundamental step in the process of designing hip assistance devices and controllers that can provide better performance in terms of metabolic cost. We have developed and tested a soft exoskeleton for hip assistance, which includes three assistance modes: hip extension assistance (HEA), hip flexion assistance (HFA), and hip extension and

Compared with the rapidly growing artificial intelligence (AI) research in other branches of healthcare, the pace of developing AI capacities in dental care is relatively slow. Dental care automation, especially the automated capability for dental cone beam computed tomography (CBCT) segmentation and lesion detection, is highly needed. CBCT is an important imaging modality that is experiencing ever-growing

For practical mechanical systems, uncertainties/disturbances, such as unmodeled dynamics and frictions, are nonignorable factors. For existing control methods, these factors are usually neglected or addressed by a robust way. As a consequence, the nominal control performance of these methods is sacrificed. Moreover, there exists the chattering problem for some existing robust methods, such as sliding

Dissimilarity analysis (DISSIM) has been widely used to monitor the Gaussian processes. However, its further application is hindered due to its unavailability to non-Gaussian processes whose data do not satisfy the hypothesis of the Gaussian distributions. To sensitively detect faults and enhance understanding of the non-Gaussian processes, a Gaussian feature analytics-based DISSIM (GDISSIM) method

The IEEE Transactions on Automation Science and Engineering (T-ASE) wishes to thank the 1110 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

The current trends in personalized products drive the paradigms of production systems toward autonomous networked manufacturing systems. This article proposes an ontology-based holonic event-driven architecture for implementing loosely coupled, holonic, autonomous distributed systems. The event-driven architecture (EDA) enables the services provided by different organizations and their suborganizations

Bin packing and bin covering are important optimization problems in many industrial fields, such as packaging, recycling, and food processing. The problem concerns a set of items, each with its own value, that are to be sorted into bins in such a way that the total value of each bin, as measured by the sum of its item values, is not above (for packing) or below (for covering) a given target value.

Classification of electroencephalogram-based motor imagery (MI-EEG) tasks raises a big challenge in the design and development of brain–computer interfaces (BCIs). In view of the characteristics of nonstationarity, time-variability, and individual diversity of EEG signals, a deep learning framework termed SSD-SE-convolutional neural network (CNN) is proposed for MI-EEG classification. The framework

Among the characteristic symptoms of schizophrenia, negative symptoms are a category. The existence of negative symptoms results in a diminution of normal behaviors and functions for schizophrenic patients. In this research, we focus on the affective flattening of negative symptoms to explore potential biomarkers to achieve automatic diagnosis. This work proposes an automatic procedure for detecting

Sensor scheduling for energy-efficient collaborative target tracking in wireless sensor networks (WSNs) is an important problem to deal with the limited network resources. With the recent development and emerging applications of energy acquisition technologies, it has become possible to overcome the bottleneck of battery energy in WSNs using the energy harvesting devices, where theoretically the lifetime

Industry 4.0 production systems must support flexibility in various dimensions, such as for the products to be produced, for the production processes to be applied, and for the available machinery. In this article, we present a novel approach to design and control smart manufacturing systems. The approach is reactive, that is responds to unplanned situations and implements an iterative refinement technique

This article addresses a real-world tactical production planning problem in which a series of real-world constraints need to be considered, such as no backorder, products with multilevel bills of material (BOMs), and lot streaming production. Under the premise of no backorder, the objective of this plan is to make the workload as balanced as possible throughout the planning horizon. An integer quadratic

This article describes a Voronoi-based path generation (VPG) algorithm for an energy-constrained mobile robot, such as an unmanned aerial vehicle (UAV). The algorithm solves a variation of the coverage path-planning problem where complete coverage of an area is not possible due to path-length limits caused by energy constraints on the robot. The algorithm works by modeling the path as a connected network

The mean time between failures (MTBF) and mean time to repair (MTTR) of manufacturing equipment (e.g., machines) are used in every quantitative method for production systems performance analysis, continuous improvement, and design. Unfortunately, the literature offers no methods for evaluating the smallest number of up- and downtime measurements necessary and sufficient to calculate reliable estimates

Maximum dorsiflexion (MDF) is an important gait event corresponding to the maximum ankle dorsiflexion angle in each gait cycle. MDF timing plays an important role in the control of robotic prosthesis. This article puts forward an on-board adaptive algorithm to detect MDF timing of robotic transtibial prosthesis in different walking conditions (at different speeds and on different ramps) and for different

An improved method for solving conflict-free scheduling and routing of automated guided vehicles is proposed in this article, with promising results. This is achieved by reformulating the mathematical model of the problem, including several improvements and speedup strategies of an existing Benders decomposition method. A new heuristic is also presented that quickly yields high-quality solutions. Moreover

Quality control is the key for the widespread adoption of metal additive manufacturing (AM). However, online quality estimation is challenging because high-frequency stream data derived from in situ metrology have to be processed in a timely manner to figure out the complicated interactions among material, machine, and part. To tackle such issue, this article proposes an intelligent AM metrology (IAMM)

This article presents a fixed-time accommodation strategy of actuator faults for hypersonic gliding vehicles (HGVs). The approach against actuator faults is incorporated by sliding mode control (SMC), bilimit homogeneity, and adaptive techniques, with consideration of practical constraints and model uncertainties. The resulting fault-tolerant attitude control law allows the fault compensation to be

Timed Petri nets (TPNs) have been widely used for modeling discrete-event systems of diverse manufacturing and service industries. In this article, we introduce a reachability tree-based optimization algorithm to optimize cyclic schedules of TPNs. In particular, we focus on a special class of cyclic schedules that are referred to as one-cyclic schedules, i.e., the algorithm efficiently finds the optimal

This article deals with improved formal verification of reconfigurable discrete-event systems (DESs) modeled by reconfigurable timed net condition event systems (R-TNCESs). An R-TNCES consists of a set of timed net condition event systems, each of which represents a particular behavior of a DES, and a reconfiguration scenario is a switching mode from a timed net condition event system to another. However

Automation engineering is the task of integrating, via software, various sensors, actuators, and controls to automate a real-world process. Today, automation engineering is supported by a suite of software tools, including integrated development environments (IDEs), hardware configurators, compilers, and runtimes. These tools focus on the automation code itself but leave the automation engineer unassisted

A novel radio frequency identification (RFID)-based mobile robot global localization method combining two kinds of RFID signal information, i.e., phase difference and readability, is proposed. Specifically, a phase difference model and a classification logic strategy based on readability are built and integrated into a particle filter localization algorithm. Compared with existing RFID localization

Edge computing is a new architecture to provide computing, storage, and networking resources for achieving the Internet of Things. It brings computation to the network edge in close proximity to users. However, nodes in the edge have limited energy and resources. Completely running tasks in the edge may cause poor performance. Cloud data centers (CDCs) have rich resources for executing tasks, but they

In practical systems, due to reasons such as sensor limitations, sensor faults, and packet losses in networks, the observation of events becomes nondeterministic. In this article, we extend strong detectability and weak detectability to the case of nondeterministic observations and denote them as A-( $k_{1}$ , $k_{2}$ )-detectability and O-( $k_{1}$ , $k_{2}$ )-detectability, respectively. A-( $k_{1}$

The roll-to-roll (R2R) web printing system is a complex coupling system, in which tension fluctuation is caused by upstream register control, thus results in downstream register errors. Therefore, it is indispensable to compensate for the couplings in order to improve the register precision in R2R printing systems. However, existing control methods do not realize complete decoupling due to their indirect