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Paperwork has always been a central part of bureaucratic work. Over the last few years, bureaucratic procedures have become increasingly standardised and digitalised. Based on interviews and ethnographic fieldwork within welfare offices in Switzerland and Belgium, we reflect on the way evidence is constructed within social policy and cases built for or against noncitizen welfare recipients in order to show how paper truths are established and challenged. The focus on digital practices within public policy implementation highlights how it contributes to enhanced control mechanisms on the implementation level and how migration law continues to guide welfare governance for noncitizens. This allows targeting of the most marginalised groups, whose rights to access state support are institutionally impeded. Through database information flows, official forms, paper reports and face-to-face meetings, we further show how a hybrid form of bureaucratic work emerges, where direct contact with the client is still key, yet highly influenced by standardisation processes. [ABSTRACT FROM AUTHOR]

Rapid technological change – the digitalization and automation of work – is challenging contemporary welfare states. Most of the existing research, however, focuses on its effect on labor market outcomes, such as employment or wage levels. In contrast, this paper studies the implications of technological change for welfare state attitudes and preferences. Compared to previous work on this topic, this paper adopts a much broader perspective regarding different kinds of social policy. Using data from the European Social Survey, we find that individual automation risk is positively associated with support for redistribution, but negatively with support for social investment policies (partly depending on the specific measure of automation risk that is used), while there is no statistically significant association with support for basic income. We also find a moderating effect of the overall size of the welfare state on the micro-level association between risk and preferences. [ABSTRACT FROM AUTHOR]

The rate of innovation in Information Technology (IT) has slowed down over time. The slowdown is evident both in the data on quality-adjusted prices of computers, and performance of microprocessors used in computers. The model in this paper shows that an IT–labor elasticity of substitution that is greater than 1 can explain the slowdown. With an elasticity of substitution greater than 1, however, slowing innovation can result in sustained labor productivity and output growth. Sustained growth is possible because an IT–labor elasticity of substitution greater than 1 results in a continuously increasing share of IT in production costs, which counteracts the effect of slowing innovation on labor productivity and output growth. In this environment of slowing innovation, increasing IT share and sustained growth, employment can increase or decrease, depending on the values of the IT–labor elasticity of substitution and the price elasticity of demand for IT-enabled consumption goods. [ABSTRACT FROM AUTHOR]

Although several studies have revealed that fractional order controllers usually outperform conventional integer-order control solutions, fractional order controllers are not yet widely applied in industrial applications due to their complex mathematical background. In this paper, further improvements of a simple weighted sum feedback design are introduced that imitates the behavior of a fractional order controller but is free from its various formal restrictions. The proposed control solution has the main characteristics of a fractional order controller, such as finite memory length, excellent transient response with no overshoot and robust behavior, but it is placed into a much simpler mathematical framework. In the current paper, a simple derivative term was incorporated in the design which made the controller's output more stable by completely eliminating output chattering. The proposed control method was developed for a general second-order system. It was tested in a fixed point iteration-based adaptive control scenario, through simulations using a robotic example and on experimental basis as well, utilizing a simple one-degree-of-freedom electromechanical system. The presented experiments are the first systematic investigations of the fixed point iteration-based adaptive control method. [ABSTRACT FROM AUTHOR]

SUMMARY: The authors summarize the main dynamic balancing methods of robotic mechanisms in this paper. The majority of dynamic balancing methods have been presented, and there may be other dynamic balancing methods that are not included in this paper. Each of the balancing methods is reviewed and discussed. The advantages and disadvantages of each method are presented and compared. The goal of this paper is to provide an overview of recent research in balancing. The authors hope that this study can provide an informative reference for future research in the direction of dynamic balancing of robotic mechanisms. [ABSTRACT FROM AUTHOR]

With the development of intelligent manufacturing, more and more nonstandard parts are used in high-precision assembly. The robotic assembly method based on attractive region in environment (ARIE) has been proven to have good performance in the high-precision assembly under the limitation of robot system accuracy or sensing accuracy. However, for the assembly of nonstandard parts, especially nonconvex parts, the existing ARIE-based strategy lacks a targeted design. In the assembly process, the nonconvex structure may cause blocking problems, which will lead to assembly failure when using the strategy. In order to solve this problem, this paper proposes a new assembly method by using the geometric features of constraint region based on the concept of ARIE. Specifically, first, when using the ARIE-based classic strategy, the reasons for the possible blocking problem in the assembly of a class of nonconvex axisymmetric parts are analyzed in detail. Second, a multi-step sliding strategy is proposed based on the theory of ARIE to solve the possible blocking problem in the assembly process. Third, impedance control is used to enable the peg to achieve the desired compliant motion in the proposed strategy. The improvement in the success rate of the proposed method is verified by the comparison experiment of small clearance peg-in-hole assembly, where the structure of the peg is nonconvex and axisymmetric. [ABSTRACT FROM AUTHOR]

We clarify two pointsmade in our commentary (Pezzo&Beckstead, 2020, this issue) on a recent paper by Longoni, Bonezzi, and Morewedge (2019). In both Experiments 1 and 4 from their paper, it is not possible to determine whether accuracy can compensate for algorithm aversion. Experiments 3A-C, however, do show a strong effect of accuracy such that AI that is superior to a human provider is embraced by patients. Many papers, including Longoni et al. tend to minimize the role of this compensatory process, apparently because it seems obvious to the authors (Longoni, Bonezzi, Morewedge, 2020, this issue). Such minimization, however, can lead to (mis)citations in which research that clearly demonstrates a compensatory role of AI accuracy is cited as non-compensatory. [ABSTRACT FROM AUTHOR]

This article explores an early computer algebra system called MACSYMA – a repository of automated non-numeric mathematical operations developed at the Massachusetts Institute of Technology from the 1960s to the 1980s, to help mathematicians, physicists, engineers and other mathematical scientists solve problems and prove theorems. I examine the extensive paper-based training materials that were produced alongside the system to create its users. Would-be users were told that the system would free them from the drudgery of much mathematical labour. However, this ‘freedom’ could only be won by adapting to a highly disciplined mode of problem solving with a relatively inflexible automated assistant. In creating an automated repository of mathematical knowledge, MACSYMA developers sought to erase its social context. However, looking at the training literature, we see that the social operates everywhere, only recoded. This article uses the paper-based training materials to uncover the codes of conduct – both social and technical – that coordinated between the users, developers and machines that constituted the system. [ABSTRACT FROM AUTHOR]

Instrument delivery is critical part in vascular intervention surgery. Due to the soft-body structure of instruments, the relationship between manipulation commands and instrument motion is non-linear, making instrument delivery challenging and time-consuming. Reinforcement learning has the potential to learn manipulation skills and automate instrument delivery with enhanced success rates and reduced workload of physicians. However, due to the sample inefficiency when using high-dimensional images, existing reinforcement learning algorithms are limited on realistic vascular robotic systems. To alleviate this problem, this paper proposes discrete soft actor-critic with auto-encoder (DSAC-AE) that augments SAC-discrete with an auxiliary reconstruction task. The algorithm is applied with distributed sample collection and parameter update in a robot-assisted preclinical environment. Experimental results indicate that guidewire delivery can be automatically implemented after 50k sampling steps in less than 15 h, demonstrating the proposed algorithm has the great potential to learn manipulation skill for vascular robotic systems. [ABSTRACT FROM AUTHOR]

Oceans will play a crucial role in our efforts to combat the growing climate emergency. Researchers have proposed several strategies to harness greener energy through oceans and use oceans as carbon sinks. However, the risks these strategies might pose to the ocean and marine ecosystem are not well understood. It is imperative that we quickly develop a range of tools to monitor ocean processes and marine ecosystems alongside the technology to deploy these solutions on a large scale into the oceans. Large arrays of inexpensive cameras placed deep underwater coupled with machine learning pipelines to automatically detect, classify, count, and estimate fish populations have the potential to continuously monitor marine ecosystems and help study the impacts of these solutions on the ocean. In this paper, we successfully demonstrate the application of YOLOv4 and YOLOv7 deep learning models to classify and detect six species of fish in a dark artificially lit underwater video dataset captured 500 m below the surface, with a mAP of 76.01% and 85.0%, respectively. We show that 2,000 images per species, for each of the six species of fish is sufficient to train a machine-learning species classification model for this low-light environment. This research is a first step toward systems to autonomously monitor fish deep underwater while causing as little disruption as possible. As such, we discuss the advances that will be needed to apply such systems on a large scale and propose several avenues of research toward this goal. [ABSTRACT FROM AUTHOR]

Large-scale multiplex tissue analysis aims to understand processes such as development and tumor formation by studying the occurrence and interaction of cells in local environments in, for example, tissue samples from patient cohorts. A typical procedure in the analysis is to delineate individual cells, classify them into cell types, and analyze their spatial relationships. All steps come with a number of challenges, and to address them and identify the bottlenecks of the analysis, it is necessary to include quality control tools in the analysis workflow. This makes it possible to optimize the steps and adjust settings in order to get better and more precise results. Additionally, the development of automated approaches for tissue analysis requires visual verification to reduce skepticism with regard to the accuracy of the results. Quality control tools could be used to build users’ trust in automated approaches. In this paper, we present three plugins for visualization and quality control in large-scale multiplex tissue analysis of microscopy images. The first plugin focuses on the quality of cell staining, the second one was made for interactive evaluation and comparison of different cell classification results, and the third one serves for reviewing interactions of different cell types. [ABSTRACT FROM AUTHOR]

Many, especially low-skilled workers, blame globalization for their economic woes. Robots and machines, which have led to job market polarization, rising income inequality, and labor displacement, are often viewed much more forgivingly. This paper argues that citizens have a tendency to misattribute blame for economic dislocations toward immigrants and workers abroad, while discounting the effects of technology. Using the 2016 American National Elections Studies, a nationally representative survey, I show that workers facing higher risks of automation are more likely to oppose free trade agreements and favor immigration restrictions, even controlling for standard explanations for these attitudes. Although pocket-book concerns do influence attitudes toward globalization, this study calls into question the standard assumption that individuals understand and can correctly identify the sources of their economic anxieties. Accelerated automation may have intensified attempts to resist globalization. [ABSTRACT FROM AUTHOR]

In this paper, the influence of the cutting plane as well as the orientation of the cavities in cross-coupled W-band waveguide filters are investigated. When waveguide filters are manufactured with the commonly known CNC (computer numerical control) milling technique, at least one cutting plane is required. The position of this cutting plane has an impact on the composition of the cavities, the manufacturing accuracy, and on the maximal number of transmission zeros (TZs) introduced by a direct source to load (SL) cross-coupling. Similar filter set-ups therefore may show different performances depending on the position of this cutting plane. To examine all these effects, three similar fourth-order W-band filter set-ups are realized with distinct cutting planes and different oriented cavities. The filters are compared in terms of the sensitivity to manufacturing tolerances, the maximal number of TZs introduced by a direct SL cross-coupling as well as their spurious mode performance. [ABSTRACT FROM AUTHOR]

This paper presents a deep-learning-based workflow to detect synapses and predict their neurotransmitter type in the primitive chordate Ciona intestinalis (Ciona) electronmicroscopic (EM) images. Identifying synapses fromEMimages to build a fullmap of connections between neurons is a labor-intensive process and requires significant domain expertise. Automation of synapse classificationwould hasten the generation and analysis of connectomes. Furthermore, inferences concerning neuron type and function fromsynapse features are inmany cases difficult tomake. Finding the connection between synapse structure and function is an important step in fully understanding a connectome. Class ActivationMaps derived fromthe convolutional neural network provide insights on important features of synapses based on cell type and function. The main contribution of this work is in the differentiation of synapses by neurotransmitter type through the structural information in their EM images. This enables the prediction of neurotransmitter types for neurons in Ciona, which were previously unknown. The prediction model with code is available on GitHub. [ABSTRACT FROM AUTHOR]

This paper presents a bioinspiration approach that is able to scalably leverage the ever-growing body of biological information in natural-language format. The ideation tool AskNature, developed by the Biomimicry 3.8 Institute, is expanded with an algorithm for automated classification of biological strategies into the Biomimicry Taxonomy, a three-level, hierarchical information structure that organizes AskNature's database. In this way, the manual work entailed by the classification of biological strategies can be alleviated. Thus, the bottleneck is removed that currently prevents the integration of large numbers of biological strategies. To demonstrate the feasibility of building a scalable bioideation system, this paper presents tests that classify biological strategies from AskNature's reference database for those Biomimicry Taxonomy classes that currently hold sufficient reference documents. [ABSTRACT FROM AUTHOR]

SUMMARY: The particularity of nuclear power plant environment requires that the nuclear power inspection robot must be remote control operation. The main purpose of the inspection robot is to carry out inspection, prevention, reporting, and safety emergency operation on the instruments, so as to provide guarantee for the safe operation of the nuclear power plant. Based on the representative configuration of nuclear power robot at home and abroad, this paper develops a small and lightweight nuclear power plant inspection robot, including walking mechanism, lifting mechanism, operating mechanism, image acquisition, information communication and control system, etc., to carry on the statics analysis to the key components of the inspection robot and verify that the stiffness and strength of the mechanical structure meet the requirements of lightweight design. Modal analysis is carried out to verify that the motor does not cause resonance when working. The kinematic model of the robot has been established and can provide the theoretical basis for the controller design. A hierarchical control system based on LabVIEW upper computer monitoring and control operation interface is established, which uses adaptive fuzzy Proportional Integral Derivative (PID) control to simulate the walking control, and then realizes the control of walking mechanism through software programming, and the adaptive fuzzy PID control has better effect than the conventional PID control. The S-type acceleration and deceleration algorithm is used to realize the accurate control of the position location of the lifting mechanism. Finally, combined with the experiment of 5MS robot comprehensive experimental platform, it is proved that the inspection robot can realize remote control function operation. [ABSTRACT FROM AUTHOR]

Autonomous operation of mechanical systems often requires the ability to detect and locate a particular phenomenon occurring in the surrounding environment. Being implemented to articulated manipulation, such a capability may realize a wide range of applications in autonomous maintenance and repair. This paper presents the sensor-driven task space control of an end-effector that combines the field estimation and the target tracking in an unknown spatial field of interest. The radial basis function network is adopted to model spatial distribution of an environmental phenomenon as a scalar field. Their weight parameters are estimated by a recursive least square method using collective measurements from the on-board sensors mounted to the manipulator. Then the asymptotic source tracking has been achieved by the control law based on the gradient of the estimated field. A new singularity tolerant scheme has been suggested to command the task space control law despite singular configurations. Simulation results using the three-link planar robot and the 6-revolute elbow manipulator are presented to validate the main ideas. [ABSTRACT FROM AUTHOR]

SLAM is a well-studied technique for robots to build a map of environments while at the same time keeping track of their pose (position and orientation). However, SLAM does not provide motion control approaches for how the robot explores the environment. This paper presents an integrated approach to create a fully autonomous exploring and mapping robot. An Extended Kalman Filter (EKF)-SLAM approach is used to fuse Advanced Sonar measurements and the results of Laser Polar Scan Matching. The inclusion of Advanced Sonar data tackles the problem of map drifts in environments where lasers do not supply sufficient information, such as along a corridor. In addition, the proposed exploration strategy takes advantage of the characteristic of the Voronoi graph to enable the robot to strategically explore the environment in a loop-closing fashion and a safe manner. By revisiting areas to close loops as early as possible, the robot builds a more stable map incrementally while still reliably tracking its pose. Experimental results of the integrated approach are shown to demonstrate the paper's approach that provides real-time exploration of a mobile robot in an initially unknown real environment. Experimental map quality comparisons using exploration strategies show the benefits of early local loop-closing. [ABSTRACT FROM PUBLISHER]

This paper presents a distributed multiple mobile robots framework which allows programming and control of virtual and real mobile robots. The system provides the map building, path planning, robot task planning, simulation, and actual robot control functions in an indoor environment. Users can program the virtual robots in a customized simulation environment and check the performance of execution, i.e., if the simulation result is satisfying, users can download the code to a real robot. The paper focuses on the distributed architecture and key technologies of virtual robots simulation and control of real robots. A method for construction and transfer of a key index value (which stores the robot configuration) is proposed. Using this method, only the robot key configuration index is needed to build the robot in the virtual environment. This results in reduced network load and improved real time performance of the distributed system. Experiments were conducted to compare the performance of the proposed system with the performance of a centralized system. The results show that the distributed system uses less system resources and has better real time performance. What is more, this framework has been applied to Yaskawa's robot "SmartPal." The simulation and experiment results show that our robotic framework can simulate and control the robot to perform complex tasks. [ABSTRACT FROM AUTHOR]

SUMMARY: This paper investigates artificial neural network (ANN)-based simulators as an alternative to physics-based approaches for evolving controllers in simulation for a complex snake-like robot. Prior research has been limited to robots or controllers that are relatively simple. Benchmarks are performed in order to identify effective simulator topologies. Additionally, various controller evolution strategies are proposed, investigated and compared. Using ANN-based simulators for controller fitness estimation during controller evolution is demonstrated to be a viable approach for the high-dimensional problem specified in this work. [ABSTRACT FROM AUTHOR]

Summary: The paper reports on a new multi-view algorithm that combines information from multiple images of a single target object, captured at different distances, to determine the identity of an object. Due to the use of global feature descriptors, the method does not involve image segmentation. The performance of the algorithm has been evaluated on a binary classification problem for a data set consisting of a series of underwater images. [ABSTRACT FROM AUTHOR]

Background: The field of otology is increasingly at the forefront of innovation in science and medicine. The inner ear, one of the most challenging systems to study, has been rendered much more open to inquiry by recent developments in research methodology. Promising advances of potential clinical impact have occurred in recent years in biological fields such as auditory genetics, ototoxic chemoprevention and organ of Corti regeneration. The interface of the ear with digital technology to remediate hearing loss, or as a consumer device within an intelligent ecosystem of connected devices, is receiving enormous creative energy. Automation and artificial intelligence can enhance otological medical and surgical practice. Otology is poised to enter a new renaissance period, in which many previously untreatable ear diseases will yield to newly introduced therapies. Objective: This paper speculates on the direction otology will take in the coming decades. Conclusion: Making predictions about the future of otology is a risky endeavour. If the predictions are found wanting, it will likely be because of unforeseen revolutionary methods. [ABSTRACT FROM AUTHOR]

When some steps of a complex, multi-step task are automated, the demand for human work in the remaining complementary sub-tasks goes up. In contrast, when the task is fully automated, the demand for human work declines. Upon aggregation to the macroeconomic scale, partial automatability of complex tasks creates a bottleneck of development, where further growth is constrained by the scarcity of essential human work. This bottleneck is removed once the tasks become fully automatable. Theoretical analysis using a two-level nested constant elasticity of substitution production function specification demonstrates that the shift from partial to full automation generates a non-convexity: humans and machines switch from complementary to substitutable, and the share of output accruing to human workers switches from an upward to a downward trend. This process has implications for inequality, the risk of technological unemployment, and the likelihood of a secular stagnation. [ABSTRACT FROM AUTHOR]

Autonomous mobile robots need accurate localization techniques to perform assigned task. Radio Frequency Identification Technology (RFID) has become one of the main means to construct a real-time localization system. Localization techniques in RFID rely on accurate estimation of the read range between the reader and the tags. This paper proposes an auto-localization system for indoor mobile robot using passive RFID. The proposed system reads any three different RFID tags which have a known location. The current location can be estimated using the Time Difference of Arrival (TDOA) scheme. In order to improve the system accuracy, the proposed system fuses the TDOA scheme for the three tags. A Kalman filter is used to minimize the estimated error and predict the next location. The simulation results validate the proposed framework. [ABSTRACT FROM PUBLISHER]

Technological change has squeezed the demand for middle-skill jobs, which typically involve routine-intense tasks. This squeeze has coincided with an increase in the number of part-time working individuals who wish to work more hours. We argue that these two trends are linked. Due to the decline of middle-skill employment, medium-educated workers shift into low-skill employment, increasing the supply of labour for jobs in this segment of the labour market. This pushes those dependent on these jobs to accept part-time jobs, even if these involve fewer hours than they prefer. To empirically assess this claim, we analyse involuntary part-time employment across 16 European countries between 1999 and 2010. Our analysis confirms that a decline in middle-skill employment is associated with an increase in involuntary part-time employment at the bottom end of the labour market. This finding implies that the automation of routine-intense labour worsens employment possibilities in this segment of the labour market. However, we show that training and job creation schemes mitigate this effect. These programmes cushion competition either by providing medium-educated workers with the necessary skills to shift into high-skill jobs or by increasing employment possibilities. Thus, governments have the tools to support workers facing challenges in the knowledge economy. [ABSTRACT FROM AUTHOR]

The goal of the work reported in this paper is to use automated, combinatorial synthesis to generate alternative solutions to be used as stimuli by designers for ideation. FuncSION, a computational synthesis tool that can automatically synthesize solution concepts for mechanical devices by combining building blocks from a library, is used for this purpose. The objectives of FuncSION are to help generate a variety of functional requirements for a given problem and a variety of concepts to fulfill these functions. A distinctive feature of FuncSION is its focus on automated generation of spatial configurations, an aspect rarely addressed by other computational synthesis programs. This paper provides an overview of FuncSION in terms of representation of design problems, representation of building blocks, and rules with which building blocks are combined to generate concepts at three levels of abstraction: topological, spatial, and physical. The paper then provides a detailed account of evaluating FuncSION for its effectiveness in providing stimuli for enhanced ideation. [ABSTRACT FROM AUTHOR]

This paper presents an integrated design and costing method for large stiffened panels for the purpose of investigating the influence and interaction of lay-up technology and production rate on manufacturing cost. A series of wing cover panels (~586kg, 19-9m²) have been sized with realistic requirements considering manual and automated lay-up routes. The integrated method has enabled the quantification of component unit cost sensitivity to changes in annual production rate and employed equipment maximum deposition rate. Moreover the results demonstrate the interconnected relationship between lay-up process and panel design, and unit cost. The optimum unit cost solution when using automated lay-up is a combination of the minimum deposition rate and minimum number of lay-up machines to meet the required production rate. However, the location of the optimum unit cost, at the boundaries between the number of lay-up machines required, can make unit cost very sensitive to small changes in component design, production rate, and equipment maximum deposition rate. [ABSTRACT FROM AUTHOR]

The present paper addresses the issues that should be covered in order to develop walk-through programming techniques (i.e. a manual guidance of the robot) in an industrial scenario. First, an exact formulation of the dynamics of the tool the human should feel when interacting with the robot is presented. Then, the paper discusses a way to implement such dynamics on an industrial robot equipped with an open robot control system and a wrist force/torque sensor, as well as the safety issues related to the walk-through programming. In particular, two strategies that make use of admittance control to constrain the robot motion are presented. One slows down the robot when the velocity of the tool centre point exceeds a specified safety limit, the other one limits the robot workspace by way of virtual safety surfaces. Experimental results on a COMAU Smart Six robot are presented, showing the performance of the walk-through programming system endowed with the two proposed safety strategies. [ABSTRACT FROM PUBLISHER]

This paper presents a novel system for human–robot interaction in object-grasping applications. Consisting of an RGB-D camera, a projector and a robot manipulator, the proposed system provides intuitive information to the human by analyzing the scene, detecting graspable objects and directly projecting numbers or symbols in front of objects. Objects are detected using a visual attention model that incorporates color, shape and depth information. The positions and orientations of the projected numbers are based on the shapes, positions and orientations of the corresponding objects. Users select a grasping target by indicating the corresponding number. Projected arrows are then created on the fly to guide a robotic arm to grasp the selected object using visual servoing and deliver the object to the human user. Experimental results are presented to demonstrate how the system is used in robot grasping tasks. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of adaptive position tracking for a multi-link robot driven by two opposing pneumatic muscle groups with additive disturbances. In contrast to widely used sliding mode control methods, the proposed controller is continuous and able to prevent chattering. All physical parameters of the robot and the pneumatic muscles, including pneumatic muscle coefficients, link lengths and moments of inertia are unknown and can be time-varying and the unknown additive disturbances can be discontinuous. Under these conditions, we prove that closed-loop trajectories of all of the joint positions can track any C1 joint reference signal. The joint errors will be within a prescribed error bound in a finite time. The adaptive controller only uses the reference signal, not its derivative. The continuous adaptive gain is one-dimensional. Simulations including a two-link robot arm with friction and realistic muscle models are presented to demonstrate the robustness of the adaptive control under severe changes of the system parameters. In all simulations, the joint positions can track C1 trajectories and all errors are within the prescribed error bound in the same time frame, even though the muscle parameters are vastly different. [ABSTRACT FROM AUTHOR]

We assess the long-run growth effects of automation in the overlapping generations framework. Although automation implies constant returns to capital and, thus, an AK production side of the economy, positive long-run growth does not emerge. The reason is that automation suppresses wage income, which is the only source of investment in the overlapping generations model. Our result stands in sharp contrast to the representative agent setting with automation, where sustained long-run growth is possible even without technological progress. Our analysis therefore provides a cautionary tale that the underlying modeling structure of saving/investment decisions matters for the derived economic impact of automation. In addition, we show that a robot tax has the potential to raise per capita output and welfare at the steady state. However, it cannot induce a takeoff toward positive long-run growth. [ABSTRACT FROM AUTHOR]

Does the threat of automation of workers’ employment provoke distinct policy preferences from that of globalization? We present hypotheses about how these different threats affect support for policies to prevent such shocks as well as policies to compensate via redistribution. Using vignettes and conjoint experiments embedded in survey evidence from Spain, we find that the threat of automation does not provoke any greater demand for redistribution than does openness. Nor does job loss due to automation provoke beliefs of greater deservingness of compensatory transfers, compared to job loss from openness. While the threat of offshoring and hiring foreign workers increases support for policies to prevent this process from occurring, scenarios of robot substitution do not provoke a similar reaction. These results suggest policies to prioritize automation over openness may gain less political traction. [ABSTRACT FROM AUTHOR]

This paper focuses on computer-based generative methods for layout problems in architecture and urban planning with special regard for the hierarchical structuring of layout elements. The generation of layouts takes place using evolutionary algorithms, which are used to optimize the arrangement of elements in terms of overlapping within a given boundary and the topological relations between them. In this paper, the approach is extended by a data structure that facilitates the hierarchical organization of layout elements making it possible to structure and organize larger layout problems into subsets that can be solved in parallel. An important aspect for the applicability of such a system in the design process is an appropriate means of user interaction. This depends largely on the calculation speed of the system and the variety of viable solutions. These properties are evaluated for hierarchical as well as for nonhierarchical structured layout problems. [ABSTRACT FROM PUBLISHER]

This paper synthesizes protocol measurements for Ultra High Frequency (UHF) radiofrequency identification (RFID) tags’ performance. We introduce the main parameters allowing the evaluation of an inlay tag performances. We characterize all devices implemented on the test bench. We explain the different programs and all methods used for the software automation. Finally, we studied the variation of the measured parameters as a function of power, frequency, or tag orientation, both in free space and in disturbed environment through our automated test bench [ABSTRACT FROM PUBLISHER]

Restoration of mechanical energy dissipating on impact at the ground is necessary for sustainable gait generation. Parametric excitation is one approach to restore the mechanical energy. Asano et al. ("Parametric excitation mechanisms for dynamic bipedal walking," IEEE International Conference on Robotics and Automation (2005) pp. 611-617.) applied parametric excitation to a biped robot with telescopic-legs, in which up-and-down motion restores total mechanical energy like playing on the swing. In this paper, parametric excitation principle is applied to a kneed biped robot with only knee actuation and it is shown that the robot walks successively without hip actuation. We also examine influences of several parameters and reference trajectory on walking performance. [ABSTRACT FROM AUTHOR]

This paper demonstrates how numerical optimization techniques can efficiently be used to create self-stable running motions for a human-like robot model. Exploitation of self-stability is considered to be a crucial factor for biological running and might be the key for success to make bipedal and humanoid robots run in the future. We investigate a two-dimensional simulation model of running with nine bodies (trunk, thighs, shanks, feet, and arms) powered by external moments at all internal joints. Using efficient optimal control techniques and stability optimization, we were able to determine model parameters and actuator inputs that lead to fully open-loop stable running motions. [ABSTRACT FROM AUTHOR]

SUMMARYRecent advances in simultaneous localization and mapping permit robots to autonomously explore enclosed environments and, subsequently, navigate to selected positions within them. But, for many tasks, it is more useful to immediately navigate to goals in unexplored environments, without a map. This is possible if a human director can describe the ideal route to the robot using grounded symbols that both parties can perceive directly.In this paper, a mobile robot is autonomously navigated to many locations in a cluttered laboratory environment by a variety of routes. A series of topological navigation instructions are provided in advance by the director, in a form that can be expressed verbally and translates easily to software representation. The instructions are based on the perception of spatial affordances available to the robot, namely nearby junctions and edges in a pruned Generalized Voronoi Diagram. The operator can generate the instructions by viewing or imagining the environment without any measurements. Only three to five instructions are needed to navigate anywhere in our laboratory. The instructions contain only topology. No spatial measurements or environmental data such as landmarks are provided to the robot. [ABSTRACT FROM AUTHOR]

The intention of this paper is to contribute towards a unified understanding of the basic notions and terms in the domain of humanoid robotics, having in mind that the same notions are sometimes interpreted in different ways (some interpretations are contradictory, and some even erroneous). Hence, the first part of the paper is devoted to defining some basic notions, walk and gait being among the first. Then, the paper deals with the notion of dynamic balance and stability, particularly the difference between them, since these essentially different notions are often confused and, rarely, regarded as identical. As dynamic balance is directly related to the notion of zero-moment point (ZMP), it was necessary to touch upon some misunderstandings concerning the ZMP. Gait stability is an especially delicate category, as humanoid locomotion systems have certain specific features that are not possessed by other systems. Namely, because of external disturbances, there may appear unpowered (passive) degrees of freedom that cause loss of dynamic balance. Hence, these unpowered degrees of freedom cannot be overlooked in the stability analysis. As the stability of motion of humanoid robots is inseparably linked with control, it was also necessary to pay due attention to this notion. Finally, the paper ends with a discussion of posture and postural stability with all their specificities. The authors hope that this paper will contribute to a clearer understanding of the basic notions of humanoid robotics, especially concerning robots with high dynamic and control performances. [ABSTRACT FROM AUTHOR]

In this paper, the authors use the conformal geometric algebra in robotics. This paper computes the inverse kinematics of a robot arm and the differential kinematics of a pan–tilt unit using a language of spheres showing how we can simplify the complexity of the computations.This work introduces a new geometric Jacobian in terms of bivectors, which is by far more effective in its representation as the standard Jacobian because its derivation is done in terms of the projections of the involved points onto the line axes. Furthermore, unlike the standard formulation, our Jacobian can be used for any kind of robot joints.In this framework, we deal with various tasks of three-dimensional (3D) object manipulation, which is assisted by stereo-vision. All these computations are carried out using real images captured by a robot binocular head, and the manipulation is done by a five degree of freedom (DOF) robot arm mounted on a mobile robot. In addition to this, we show a very interesting application of the geometric Jacobian for differential control of the binocular head. We strongly believe that the framework of conformal geometric algebra can generally be of great advantage for visually guided robotics. [ABSTRACT FROM AUTHOR]

Reliable assessment of terrain traversability using multi-sensory input is a key issue for driving automation, particularly when the domain is unstructured or semi-structured, as in natural environments. In this paper, LIDAR-stereo combination is proposed to detect traversable ground in outdoor applications. The system integrates two self-learning classifiers, one based on LIDAR data and one based on stereo data, to detect the broad class of drivable ground. Each single-sensor classifier features two main stages: an adaptive training stage and a classification stage. During the training stage, the classifier automatically learns to associate geometric appearance of 3D data with class labels. Then, it makes predictions based on past observations. The output obtained from the single-sensor classifiers are statistically combined in order to exploit their individual strengths and reach an overall better performance than could be achieved by using each of them separately. Experimental results, obtained with a test bed platform operating in rural environments, are presented to validate and assess the performance of this approach, showing its effectiveness and potential applicability to autonomous navigation in outdoor contexts. [ABSTRACT FROM AUTHOR]

The languages accepted by finite automata are precisely the languages denoted by regular expressions. In contrast, finite automata may exhibit behaviours that cannot be described by regular expressions up to bisimilarity. In this paper, we consider extensions of the theory of regular expressions with various forms of parallel composition and study the effect on expressiveness. First we prove that adding pure interleaving to the theory of regular expressions strictly increases its expressiveness modulo bisimilarity. Then, we prove that replacing the operation for pure interleaving by ACP-style parallel composition gives a further increase in expressiveness, still insufficient, however, to facilitate the expression of all finite automata up to bisimilarity. Finally, we prove that the theory of regular expressions with ACP-style parallel composition and encapsulation is expressive enough to express all finite automata up to bisimilarity. Our results extend the expressiveness results obtained by Bergstra, Bethke and Ponse for process algebras with (the binary variant of) Kleene's star operation. [ABSTRACT FROM AUTHOR]

We clarify two points made in our commentary (Pezzo & Beckstead, 2020, this issue) on a recent paper by Longoni, Bonezzi, and Morewedge (2019). In both Experiments 1 and 4 from their paper, it is not possible to determine whether accuracy can compensate for algorithm aversion. Experiments 3A-C, however, do show a strong effect of accuracy such that AI that is superior to a human provider is embraced by patients. Many papers, including Longoni et al. tend to minimize the role of this compensatory process, apparently because it seems obvious to the authors (Longoni, Bonezzi, Morewedge, 2020, this issue). Such minimization, however, can lead to (mis)citations in which research that clearly demonstrates a compensatory role of AI accuracy is cited as non-compensatory.

This paper develops a new adaptive actuator failure compensation algorithm for the control of a cooperative robotic system subject to uncertain actuator failures. The benchmark robotic system has two manipulators to balance a rigid platform, and the right-side manipulator contains one actuator and the left-side manipulator has two actuators (one of which may fail during system operation, but it is uncertain how much, when and which actuator may fail). The developed adaptive actuator failure compensation scheme, based on adaptive integration of three individual failure compensators and direct adaptation of controller parameters, is capable of ensuring desired closed-loop stability and asymptotic output tracking, despite the failure uncertainties. Such an adaptive actuator failure compensation method is extended to control of a general cooperative robotic system. Simulation results are shown to verify the desired adaptive failure compensation control performance. [ABSTRACT FROM AUTHOR]

In this paper, aimed at dependently typed programmers, we present a novel connection between automated and interactive theorem proving paradigms. The novelty is that the connection offers a better trade-off between usability, efficiency and soundness when compared to existing techniques. This technique allows for a powerful interactive proof framework that facilitates efficient verification of finite domain theorems and guided construction of the proof of infinite domain theorems. Such situations typically occur with industrial verification. As a case study, an embedding of SAT and CTL model checking is presented, both of which have been implemented for the dependently typed proof assistant Agda.Finally, an example of a real world railway control system is presented, and shown using our proof framework to be safe with respect to an abstract model of trains not colliding or derailing. We demonstrate how to formulate safety directly and show using interactive theorem proving that signalling principles imply safety. Therefore, a proof by an automated theorem prover that the signalling principles hold for a concrete system implies the overall safety. Therefore, instead of the need for domain experts to validate that the signalling principles imply safety they only need to make sure that the safety is formulated correctly. Therefore, some of the validation is replaced by verification using interactive theorem proving. [ABSTRACT FROM PUBLISHER]

It has become a common practice to use simulation to generate large databases of good grasps for grasp planning in robotics research. However, the existence of a generic simulation context that enables the generation of high quality grasps that can be used in several different contexts such as bin-picking or picking objects from a table, has to our knowledge not yet been discussed in the literature.In this paper, we investigate how well the quality of grasps simulated in a commonly used “generic” context transfers to a specific context, both, in simulation and in the real world.We generate a large database of grasp hypotheses for several objects and grippers, which we then evaluate in different dynamic simulation contexts e.g., free floating (no gravity, no obstacles), standing on a table and lying on a table.We present a comparison on the intersection of the grasp outcome space across the different contexts and quantitatively show that to generate reliable grasp databases, it is important to use context specific simulation.We furthermore evaluate how well a state of the art grasp database transfers from two simulated contexts to a real world context of picking an object from a table and discuss how to evaluate transferability into non-deterministic real world contexts. [ABSTRACT FROM PUBLISHER]