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Designing an incentive compatible auction that maximizes expected revenue is an intricate task. The single-item case was resolved in a seminal piece of work by Myerson in 1981, but more than 40 years later, a full analytical understanding of the optimal design still remains elusive for settings with two or more items. In this work, we initiate the exploration of the use of tools from deep learning for the automated design of optimal auctions. We model an auction as a multi-layer neural network, frame optimal auction design as a constrained learning problem, and show how it can be solved using standard machine learning pipelines. In addition to providing generalization bounds, we present extensive experimental results, recovering essentially all known solutions that come from the theoretical analysis of optimal auction design problems and obtaining novel mechanisms for settings in which the optimal mechanism is unknown. [ABSTRACT FROM AUTHOR]

This paper proposes an auction-based market trade mechanism for the electric vehicle battery recycling (EVBR) problem, which aims to realise the optimal resource allocation and pricing of EVBR. The main motivation of this paper is to attempt to explore an approach to achieving efficient battery recycling. We first consider an EVBR market with m buyers and n sellers, and develop the multi-unit trade reduction (MTR) mechanism in the EVBR market. According to the supply and demand relationship in the EVBR market, we consider three market scenarios of supply and demand balance, oversupply, and overdemand, and formulated corresponding auction allocation rules. Numerical study results show that the proposed MTR mechanism can achieve efficient resource allocation. We also observed that not all results increased with the number of sellers/buyers. Second, considering the distance between sellers and buyers, we developed a stochastic multiple MTR (SM-MTR) mechanism to enable sellers and buyers within the region to conduct transactions. Finally, we propose an integrated MTR, SM-MTR and one-sided Vickrey--Clarke--Groves auction mechanism that is feasible in both one-sided and bilateral environments. Furthermore, our work can provide novel managerial implications for EVBR market stakeholders in terms of practical application. [ABSTRACT FROM AUTHOR]

This paper focuses on addressing the limitations of existing mechanical weeding methods for corn plants by introducing a spiral tendon-type precision weeding device specifically designed for corn fields. The study encompasses mechanical design and theoretical analysis to determine the overall structure, component parts, application scenarios, operation modes, and working principles of the device. The force applied to the spiral tendon weeding cutter head, a crucial working component of the device, is analyzed, along with its motion characteristics. This analysis allows for the calculation of the force required for the spiral tendon to penetrate the soil, as well as the determination of its trajectory and speed in the soil. The desired motion pattern of the weeding cutter head is considered in determining the contour shape of the inner cylinder track and its cooperation mode with the roller follower. Furthermore, the design and optimization of the circulation groove track are conducted to derive the key parameters of the track. A prototype is then constructed based on the proposed structural design and parameter optimization scheme. Soil bin tests are performed to evaluate the device's performance. The optimal combinations of working parameters are determined as follows: a 70-mm depth of the weeding cutter head into the soil, a movement speed of 80 mm/s, and an output thrust of the electric actuator of 180 N. Under these conditions, the device achieves a weed removal rate exceeding 95% with a 3% wounding rate, demonstrating stable operational performance. [ABSTRACT FROM AUTHOR]

This paper presents the development of a robotic ankle exoskeleton for human walking assistance. First, the biomechanical properties of a human ankle joint during walking are presented. Next, design of the robotic ankle exoskeleton is introduced. The exoskeleton is actuated by a novel parallel nonlinear elastic actuator. The cam-spring mechanism in the actuator can function as a parallel nonlinear spring with an adjustable stiffness, and the design of the cam profile curve is described. Additionally, an adaptive controller is proposed for the exoskeleton to generate a desired assistive torque according to the wearer's total weight. Finally, experiments are conducted to validate the effectiveness of the developed robotic ankle exoskeleton. The experimental results demonstrate that during a gait cycle, reductions of 42.7% and 40.1% of the peak and average currents of the driving motor in the actuator are observed, respectively, with the designed cam-spring mechanism. A peak assistive torque of 23.9 Nm can be provided for the wearers by the exoskeleton during walking. With the assistance provided by the exoskeleton, the average and peak soleus activities of the wearers during a gait cycle are decreased by 25.42% and 31.94%, respectively. [ABSTRACT FROM AUTHOR]

This paper studies the general principal-agent framework in which the principal aims to implement his first-best action that is monotone in the unknown state. The principal privately selects a signal structure of the agent whose payoff depends on the principal's action, the state, and the privately known type. The agent privately observes the generated signal and reports it to the principal, who takes action. We show that by randomizing between two perfectly informative signal structures, the principal can elicit perfect information from the agent about the state and implement his first-best action regardless of the agent's type. As to the economic application, we consider the bilateral trade model with non-quasilinear preferences and private multi-dimensional information of the buyer, and show that the seller can extract full surplus by privately designing the buyer's signal structures. [ABSTRACT FROM AUTHOR]

A classical result by Myerson (Math. Oper. Res. 6(1), 58-73, 1981) gives a characterization of an optimal auction for any given distribution of valuations of the bidders. We consider the situation where the distribution is not explicitly given but can be observed in a sample of auction results from the same distribution. A seminal paper by Morgenstern and Roughgarden (Adv.Neural Inf. Process. Syst. 28, 2015) proposes to learn a near-optimal auction from the hypothesis class of t-level auctions. They prove a bound on the sample complexity, i.e., the function f (ε , δ) of required samples to guarantee a certain level of precision (1 - ε) with a probability of at least (1 - δ) , for the general single-parameter case and a tighter bound for the very restricted matroid case. We show a new bound for the case of independence systems, that widely generalizes matroids and contains several important combinatorial optimization problems. This bound of O ~ H 2 n 4 ε 3 falls neatly between those known for the general and the matroid case. The class of independence systems contains several well known NP-hard problems such as knapsack. Therefore, the allocation itself might in practice be limited to α -approximate solutions. In a second result we show that an approximation algorithm can be used without compromising the sample complexity. Also, the precision is affected only mildly, resulting in a factor of α · (1 - ε) . [ABSTRACT FROM AUTHOR]

We consider a setting with agents that have preferences over alternatives and are partitioned into disjoint districts. The goal is to choose one alternative as the winner using a mechanism which first decides a representative alternative for each district based on a local election with the agents therein as participants, and then chooses one of the district representatives as the winner. Previous work showed bounds on the distortion of a specific class of deterministic plurality-based mechanisms depending on the available information about the preferences of the agents in the districts. In this paper, we first consider the whole class of deterministic mechanisms and show asymptotically tight bounds on their distortion. We then initiate the study of the distortion of randomized mechanisms in distributed voting and show bounds based on several informational assumptions, which in many cases turn out to be tight. Finally, we also experimentally compare the distortion of many different mechanisms of interest using synthetic and real-world data. [ABSTRACT FROM AUTHOR]

In this paper, we present a 3-USR-type 6-degree-of-freedom (6-DOF) parallel mechanism characterized by an expansive workspace. This mechanism consists of three coupling chains, each comprising a universal pair (U), a spherical pair (S), and a rotational pair (R), in sequence from the stationary base. To achieve a large workspace, the three stationary universal pairs are designated as active pairs, with their rotational axes intersecting at a single point, thereby creating a hemispherical workspace akin to that of a serial mechanism. To implement the active universal pair within a parallel mechanism, we replaced the spherical 5-link mechanism, which originally featured two stationary active rotational pairs, with stationary active universal pairs, and conducted an inverse kinematics analysis. Subsequently, we assessed the expansive workspace of the spherical 5-link mechanism, a key factor influencing the working area of the 3-USR-type 6-DOF parallel mechanism, by examining its motion transmissibility. Based on this evaluation, we designed two compact mechanisms that provide a large workspace and allow for the configuration of all three rotational axes to intersect at a single point. We experimentally investigated the relationship between motion transmissibility and rigidity for these two types of spherical 5-link mechanisms, demonstrating that motion transmissibility can serve as an indicator of rigidity. Finally, a prototype of the 3-USR mechanism was fabricated. [ABSTRACT FROM AUTHOR]

Contests are commonly used as a mechanism for eliciting effort and participation in multi-agent settings. Naturally, and much like with various other mechanisms, the information provided to the agents prior to and throughout the contest fundamentally influences its outcomes. In this paper we study the problem of information providing whenever the contest organizer does not initially hold the information and obtaining it is potentially costly. As the underlying contest mechanism for our model we use the binary contest, where contestants' strategy is captured by their decision whether or not to participate in the contest in the first place. Here, it is often the case that the contest organizer can proactively obtain and provide contestants information related to their expected performance in the contest. We provide a comprehensive equilibrium analysis of the model, showing that even when such information is costless, it is not necessarily the case that the contest organizer will prefer to obtain and provide it to all agents, let alone when the information is costly. [ABSTRACT FROM AUTHOR]

We study a setting where a receiver must design a questionnaire to recover a sequence of symbols known to a strategic sender, whose utility may not be incentive compatible. We allow the receiver the possibility of selecting the alternatives presented in the questionnaire, and thereby linking decisions across the components of the sequence. We show that, despite the strategic sender and the noise in the channel, the receiver can recover exponentially many sequences, but also that exponentially many sequences are unrecoverable even by the best strategy. We define the growth rate of the number of recovered sequences as the information extraction capacity. A generalization of the Shannon capacity, it characterizes the optimal amount of communication resources required while communicating with a strategic sender. We derive bounds leading to an exact evaluation of the information extraction capacity in many cases. Our results form the building blocks of a novel, non-cooperative regime of communication involving a strategic sender. • An uninformed receiver aims to recover information from an informed strategic sender • No assumption of incentive compatibility or external incentives • Information-theoretic analysis shows a fundamental limit on recovered information • Real-world setting of screening of travellers using questionnaires can be studied • Novel theory combining Shannon's information theory and Myerson's mechanism design [ABSTRACT FROM AUTHOR]

This paper proposes a deep generative model-based framework for synthesizing four-bar linkage mechanisms that satisfy specified kinematic and quasi-static conditions. We define two objective functions for crank-rocker mechanisms using kinematic workspaces and geometric configurations. Our approach utilizes a conditional generative adversarial network (cGAN) modified for mechanism synthesis, which learns the relationship between mechanism requirements and linkage lengths. The results demonstrate that the proposed model successfully generates multiple distinct mechanisms meeting specific kinematic and quasi-static requirements. We compare our cGAN approach to traditional optimization methods and other deep learning-based generative models. Our method offers several advantages over traditional design approaches, enabling efficient generation of diverse yet feasible design candidates while exploring a large design space. By considering both kinematic and quasi-static requirements, the proposed model can produce more effective mechanisms for real-world applications. This makes it a promising tool for linkage mechanism design, offering designers a way to efficiently generate multiple viable design options that satisfy key performance criteria. [ABSTRACT FROM AUTHOR]

Receiving uninterrupted videos from a scene with multiple cameras is a challenging task. One of the issues that significantly affects this task is called occlusion. In this paper, we propose an algorithm for occlusion handling in multi-camera systems. The proposed algorithm, which is called Real-time leader finder (Releaf), leverages mechanism design to assign leader and follower roles to each of the cameras in a multi-camera setup. We assign leader and follower roles to the cameras and lead the motion by the camera with the least occluded view using the Stackelberg equilibrium. The proposed approach is evaluated on our previously open-sourced tendon-driven 3D-printed robotic eye that tracks the face of a human subject. Experimental results demonstrate the superiority of the proposed algorithm over the Q-leaning and Deep Q Networks (DQN) baselines, achieving an improvement of 20 % and 18 % for horizontal errors and an enhancement of 81 % for vertical errors, as measured by the root mean squared error metric. Furthermore, Releaf has the superiority of real-time performance, which removes the need for training and makes it a promising approach for occlusion handling in multi-camera systems. [ABSTRACT FROM AUTHOR]

In this paper, we take a mechanism design approach to optimal assignment problems with asymmetrically informed buyers. In addition, the surplus generated by an assignment of a buyer to a seller may be adversely affected by externalities generated by other assignments. The problem is complicated by several factors. Buyers know their own valuations and externality costs but do not know this same information for other buyers. Buyers also receive private signals correlated with the state and, consequently, the implementation problem exhibits interdependent valuations. This precludes a naive application of the VCG mechanism and to overcome this interdependency problem, we construct a two-stage mechanism. In the first stage, we exploit correlation in the firms signals about the state to induce truthful reporting of observed signals. Given that buyers are honest in stage 1, we then use a VCG-like mechanism in stage 2 that induces honest reporting of valuation and externality functions. [ABSTRACT FROM AUTHOR]

As the range of applications of robots expanded, they began to be used for complex assemblies such as screw fastening and pin assembly. Most specialized screw fastening tools are sensitive to external influences and require additional instruments to prevent screw dislodgement when working in unstructured environments. To address this challenge, we propose a screw fastening gripper (SFG) capable of screw fastening and small pin gripping with a single power source. The proposed SFG is divided into a fastening part for screw fastening and a gripper for grasping, with power distributed via a magnetic gear. It is designed to temporarily separate the gripper and fastener using the magnetic gear's features, so it can be used to fasten screws of various lengths if necessary. Through gripping force measurements and screw fastening experiments, the proposed SFG showed sufficient performance in grasping and screw fastening. [ABSTRACT FROM AUTHOR]

This paper studies an optimal assignment problem of heterogenous students to schools with a particular kind of preference complementarity: peer effects, defined by the average ability of those in the same school. The tractability of the problem allows us to characterize the optimal assignment mechanism, which has a simple "(stochastic) pass-fail" structure. Its shape is mainly determined by the convexity/concavity of the attainment function, interpreted as the preference for/against having diverse-ability students in different schools. We also provide comparative statics as to when more or less mixture of heterogenous ability types would be desirable. [ABSTRACT FROM AUTHOR]

We study the design of optimal mechanisms when the designer is uncertain both about the form of information held by the agents and also about which equilibrium will be played. The guarantee of a mechanism is its worst performance across all information structures and equilibria. The potential of an information structure is its best performance across all mechanisms and equilibria. We formulate a pair of linear programs, one of which is a lower bound on the maximum guarantee across all mechanisms, and the other of which is an upper bound on the minimum potential across all information structures. In applications to public expenditure, bilateral trade, and optimal auctions, we use the bounding programs to characterize guarantee‐maximizing mechanisms and potential‐minimizing information structures and show that the max guarantee is equal to the min potential. [ABSTRACT FROM AUTHOR]

Abstract This paper focuses on addressing the limitations of existing mechanical weeding methods for corn plants by introducing a spiral tendon-type precision weeding device specifically designed for corn fields. The study encompasses mechanical design and theoretical analysis to determine the overall structure, component parts, application scenarios, operation modes, and working principles of the device. The force applied to the spiral tendon weeding cutter head, a crucial working component of the device, is analyzed, along with its motion characteristics. This analysis allows for the calculation of the force required for the spiral tendon to penetrate the soil, as well as the determination of its trajectory and speed in the soil. The desired motion pattern of the weeding cutter head is considered in determining the contour shape of the inner cylinder track and its cooperation mode with the roller follower. Furthermore, the design and optimization of the circulation groove track are conducted to derive the key parameters of the track. A prototype is then constructed based on the proposed structural design and parameter optimization scheme. Soil bin tests are performed to evaluate the device’s performance. The optimal combinations of working parameters are determined as follows: a 70-mm depth of the weeding cutter head into the soil, a movement speed of 80 mm/s, and an output thrust of the electric actuator of 180 N. Under these conditions, the device achieves a weed removal rate exceeding 95% with a 3% wounding rate, demonstrating stable operational performance.

Abstract Polymerase chain reaction (PCR) is an effective method for diagnosing infectious diseases and has been the primary method throughout the novel coronavirus disease (COVID-19) pandemic. PCR tests (from specimen collection to result acquisition) involve sample pretreatment, nucleic acid extraction, and PCR procedure. Automating the pretreatment process is crucial to mitigate the risk of infection for workers and to reduce the likelihood of sample contamination-triggered misdiagnosis, particularly when handling centrifuge tubes, cryopreservation tubes, and microtubes. Robotic systems have been engineered to automate cell culture and PCR-based diagnosis, predominantly designed for use with screw-capped containers. However, this leaves a notable gap in automation solutions for microtubes equipped with press-type caps. To address this gap, we developed a versatile microtube capper/decapper system. On the other hand, many tasks of manual operation using microtubes, which are routinely conducted in clinical tests and biological experiments, are performed. Compared to screw-type caps for centrifuge and cryopreservation tubes, press-type caps for microtubes present a considerably higher risk of the worker's fingers contacting the inside of the cap and/or generating airborne droplets. Despite the risks of contamination and infection derived from the manual handling of microtube caps, which can compromise diagnosis/experiment accuracy and worker safety, devices for manually opening and closing microtube caps without direct contact remain lacking. Therefore, leveraging the technology from the developed versatile microtube capper/decapper system for laboratory automation, we created a manually operated microtube equipped with an automatic capper/decapper system tailored for personnel in clinical and biological laboratories. In this study, we first examined the required specifications and prerequisites for a manual microtube capper/decapper and clarified the operating methods, operating procedures, operation environment, device size, accompanying functions, etc. Based on the required specifications and preconditions, we proceeded with the mechanical and control design of the conceptual model, manufactured a prototype, and confirmed its basic functions and performance. The compliant to the required specifications and preconditions and the usefulness of the proposed manual microtube capper/decapper were validated through various experiments and demonstrations. Using the proposed microtube capper/decapper, even small-scale operations, which are challenging to streamline, can be performed nearly as efficiently as full manual operations. Although operation time was not reduced, the ability to open and close microtubes without manual contact is crucial for improving diagnostic and experimental accuracy and for reducing the burden on and enhancing the safety of laboratory personnel. Because microtubes are used in various clinical tests and biological experiments, we believe that the proposed system can markedly reduce the workload for personnel across numerous clinical and biological laboratories.

Recent financial technologies have enabled fast payments and are reshaping retail payment and settlement systems globally. We developed an analytical model to study the optimal design of a new retail payment system in terms of settlement speed and system capability under both bank and fintech firm heterogeneous participation incentives. We found that three types of payment systems emerge as equilibrium outcomes: batch retail (BR), expedited retail (ER), and real-time retail (RR) payment systems. Although the base value of the payment service positively affects both settlement speed and system capability, the expected liquidity cost negatively impacts settlement speed, and total transaction volume and technological effectiveness positively impact system capability. We identified three leadership strategies to maximize social welfare: the government mandate (GM) strategy, the fintech-inclusive (FI) strategy, and the fintech-exclusive and bank-exclusive (FE+BE) strategy. When the base value of the payment service is either low or high, the GM strategy leads to a socially optimal unified system. When the base value of the payment service is in the intermediate range, and if fintech firms have a significant technological advantage over banks, then both GM and FI strategies result in a socially optimal unified system; otherwise, the FE+BE strategy results in a socially optimal fragmented system. Further, we proposed a Shapley-value-based cost-sharing rule under the GM strategy to fairly allocate social welfare among the system participants. Our findings offer important policy insights into the optimal system designs, leadership strategies, and the government regulator's role in shaping future innovations in the payments industry. [ABSTRACT FROM AUTHOR]

In order to solve the current problem of a single oral motion mode for the humanoid expression robot, a novel multi degree of freedom (DOF) bionic jaw mechanism was designed based on the anatomical motion mechanism of the human jaw. The inverse kinematics model of the mechanism was established, and the motion mode of the mechanism was analyzed to realize the multi DOF motion of the bionic jaw mechanism in space. A multi rigid body simulation of the bionic jaw mechanism was conducted, whose feasibility was verified by the experiments. The simulation and experimental results demonstrate that, based on the inverse kinematics model, the mechanism designed is able to simulate the three basic motion modes of human jaw, including open-close movement, protrusion movement, and side shifting movement, as well as the complex oral motion modes including chewing and lip biting. Therefore, the proposed mechanism can compensate for the limits of oral movement patterns of the existing humanoid robots.

Abstract The ankle–foot prosthesis aims to compensate for the missing motor functions by fitting the motion characteristics of the human ankle, which contributes to enabling the lower-limb amputees to take care of themselves and improve mobility in daily life. To address the problems of poor bionic motion of the ankle–foot prosthesis and the lack of natural interaction among the patient, prosthesis, and the environment, we developed a complex reverse-rolling conjugate joint based on the human ankle–foot structure and motion characteristics, the rolling joint was used to simulate the rolling-sliding characteristics of the knee joint. Meanwhile, we established a segmental dynamics model of the prosthesis in the stance phase, and the prosthetic structure parameters were obtained with the optimal prosthetic structure dimensions and driving force. In addition, a carbon fiber energy-storage foot was designed based on the human foot profile, and the dynamic response of its elastic strain energy at different thicknesses was simulated and analyzed. Finally, we integrated a bionic ankle–foot prosthesis and experiments were conducted to verify the bionic nature of the prosthetic joint motion and the energy-storage characteristics of the carbon fiber prosthetic foot. The proposed ankle–foot prosthesis provides ambulation support to assist amputees in returning to social life normally and has the potential to help improve clinical viability to reduce medical rehabilitation costs.

In contexts as diverse as civil war interventions, alliances, and military coalitions, states often militarily assist protégés to counteract unfavorable power shifts. Existing theoretical work finds that such assistance mitigates commitment problems and reduces the probability of war. We develop a model that captures this but also includes information asymmetries. In many cases, overcoming the commitment problem encourages the protégé to take greater risks in bargaining, thereby increasing the probability of war due to incomplete information. Using mechanism design, we show that in some cases, no feasible transfer can reduce the probability of war to zero. More broadly, our results indicate that encouraging policymakers to further expand military assistance can backfire despite empirical relationships that may appear otherwise. [ABSTRACT FROM AUTHOR]

In this study an innovative integrated approach is proposed to develop a design schema for automatic defect detection system. This system has been successfully implemented in an empirical factory setting. In addition, this novel design has been authorized a new patent. This integrated methodology is literally comprised of vertical thinking mode coupled with lateral mode, which results a much better solution than employing traditional way alone. The vertical mode includes DMAIC, 8D methodology, and ECRS techniques. And the lateral counter-part consists of Design Thinking and 3I Design Methodology. The empirical implementation of this integrated approach focuses on the automated defect detection of manufacturing cell phone case. The patented novel design has been proven to be empirical efficacy and effectiveness. The testing results reveal considerable savings both in labor expenditures and reduced costs. [ABSTRACT FROM AUTHOR]

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This research introduces the novel "Kraken-Gear" mechanism, emphasizing the advantages of additive polymer 3D printing in high-ratio gearbox systems for lightweight robotic applications, such as surgical instruments. The innovative kinematic solution provides high torsional system stiffness, substantial gear ratios, and backlash-free transmission. Leveraging the "hot lithography" additive manufacturing method ensures precise and warp-free gearbox components. Targeting medical technology, the gearbox meets stringent requirements: backlash-free, minimal vibration, high precision, and torque, with minimized weight for ergonomic comfort and fatigue mitigation. Computational simulations assess forces and stresses, highlighting the potential of additive manufacturing for cost-effective and functionally efficient gearbox fabrication. Nevertheless, careful material selection remains imperative for optimal functionality, especially in demanding medical applications. In summary, this research underscores a promising approach to gearbox fabrication, emphasizing the critical role of material selection and simulation-based assessments for optimal performance. [ABSTRACT FROM AUTHOR]

This paper introduces the design of an articulated wheeled robot with four links and three joints that can travel in pipes with inner diameters of 4 in with a traction force of 300 N or more. Although many in-pipe inspection robots have been reported, no examples can yet travel long distances, including many curved sections. This paper presents roller material with the best friction property and durability for in-pipe robots to possess high traction capability. Lifting payload and long distance in-pipe travel tests were also conducted for the robot with the selected elastic materials. The results demonstrate that a 16 kg weight was successfully lifted, and the robot can travel a total length of 23 m, including 19 horizontal and vertical bent sections. [ABSTRACT FROM AUTHOR]

The widespread use of cloud computing has brought cloud security to the forefront. The cloud provider and the firm assume varying degrees of joint responsibility for cloud security with cloud service models including IaaS, PaaS, and SaaS, to defend the strategic hacker. This paper builds a game-theoretical model to study cloud security management, in which we find that ignoring the strategic hacker leads to the dislocation security investment decisions (overinvestment or underinvestment) for the provider and the firm in bilateral refund contracts (BRCs). The strategic hacker's attack effort is inverse U-shaped with cloud service models, leading to a free-riding problem between the provider and the firm. Furthermore, from the perspective of social welfare maximization, both the provider and the firm would underinvest or overinvest in cloud security. To solve the problem, we propose two new contract mechanisms: one is an internal effort-based contract, in which the provider oversees the firm internally and the compensation rate depends on the firm's effort once the breach occurs. The other is an external effort-based contract, in which the monitoring agency supervises the efforts of the provider and the firm. We compare the two new contracts with BRCs and obtain the optimal choice for principals. [ABSTRACT FROM AUTHOR]

Multi-party carpooling emerges as a burgeoning shared transportation scheme whereby the trip shared by each driver is shared among multi-party riders whose itineraries coincide. Confronting the information asymmetry and the voluntary self-interested nature of bilateral participants in matching and pricing operations, this study designs M ulti-party c A rpooling S uppor T ed strat E gy-p R oof (MASTER) double auction mechanisms considering personalized carpooling constraints. First, in a scheduled carpooling scenario, two MASTER S mechanisms that masterfully blend the ideas of the famed trade reduction method and multi-stage approach are proposed which implement distinct group bid determination approaches for responding to different market conditions. Second, in an on-demand carpooling scenario, two parameterized MASTER O mechanisms that integrate frustration-based promotion to proactively prioritize matching and deferentially compensate riders based on their waits are contrived which also endow the platform with operational flexibility to agilely pursue alterable operational objectives by adjusting promotion strength. We prove theoretically that the proposed mechanisms satisfy strategy proofness, budget balance, individual rationality, and asymptotic efficiency under mild conditions. Experimental results reveal that multi-party carpooling constitutes a multi-win solution under higher rider-driver ratios whilst it could be detrimental to drivers otherwise, which can be ameliorated by favoring the driver side in determining promotion strength. Simulation studies manifest that our proposed auction mechanisms could bring benefits concerning allocation efficiency and service responsiveness compared with their academic and practical counterparts. We also shed light on choosing among alternative mechanisms according to market conditions and operational orientations. [ABSTRACT FROM AUTHOR]

I study a persuasion game between a privately informed agent and a decision maker (DM) who can imperfectly verify the statements made by the agent by observing a signal that is correlated with the agent's information. I find that whether or not the DM benefits from communicating with the agent depends on whether the DM's signal and the agent's private information satisfy a weak affiliation condition. I then discuss the significance of this result to the debate over the use of self‐appraisals in business. I argue that, in general, self‐appraisals are only useful when the workers' abilities are multidimensional. [ABSTRACT FROM AUTHOR]

We explore mechanism design with outcome‐based social preferences. Agents' social preferences and private payoffs are all subject to asymmetric information. We assume quasi‐linear utility and independent types. We show how the asymmetry of information about agents' social preferences can be operationalized to satisfy agents' participation constraints. Our main result is a possibility result for groups of at least three agents: Any such group can resolve any given allocation problem with an ex post budget‐balanced mechanism that is Bayesian incentive‐compatible, interim individually rational, and ex post Pareto‐efficient. [ABSTRACT FROM AUTHOR]

The crawler-type maintenance robot designed for the steam generator in nuclear power plants faces challenges such as inadequate adaptability and low maintenance efficiency. In order to address the task of maintaining multiple specifications of heat transfer tubes in the steam generator, a novel quadruped crawling maintenance robot with a new mechanism was proposed and gait planning was conducted. Firstly, the configuration and overall design of the robot were determined based on the requirements to adapt to multiple specifications of tube plates, and the main motion mode of the crawling robot was identified, along with providing the workspace for tools. Subsequently, research on gait planning was conducted for different types of tube plates, including planning linear motion gaits and turning motion gaits on tube plates arranged in triangular and square patterns. Finally, the motion simulation experiments of the robot were conducted through a joint simulation of V-REP and Python. The results demonstrate that the crawling robot can execute linear and turning motions on tube plates of various specifications, showcasing the rationality of the mechanism and the feasibility of the motion. [ABSTRACT FROM AUTHOR]

This paper presents a concurrent optimization approach for the design and motion of a quadruped in order to achieve energy-efficient cyclic behaviors. Computational techniques are applied to improve the development of a novel quadruped prototype. The scale of the robot and its actuators are optimized for energy efficiency considering the complete actuator model including friction, torque, and bandwidth limitations. This method and the optimal bounding trajectories are tested on the first (non-optimized) prototype design iteration showing that our formulation produces a trajectory that (i) can be easily replayed on the real robot and (ii) reduces the power consumption w.r.t. hand-tuned motion heuristics. Power consumption is then optimized for several periodic tasks with co-design. Our results include, but are not limited to, a bounding and backflip task. It appears that, for jumping forward, robots with longer thighs perform better, while, for backflips, longer shanks are better suited. To explore the tradeoff between these different designs, a Pareto set is constructed to guide the next iteration of the prototype. On this set, we find a new design, which will be produced in future work, showing an improvement of at least 52% for each separate task. [ABSTRACT FROM AUTHOR]

This study's goals are divided into two categories. The first is to design and build an excavator equipped with parallel electrical linear actuators. The second is to generate and test a PSO-based and a PFM-based path for this excavator in order to save energy by reducing energy consumption, improve the digging accuracy by minimizing the deviation between the desired and dug surfaces of the ground, and prevent colliding with subsurface objects. For this purpose, computer vision was employed to improve monitoring and verification. Five types of experiments were carried out in this investigation. The first two and the other three examined the impact of energy conservation in PSO- and PFM-based path generation, respectively. Finally, the results from these experiments were compared to identify and show the effect of optimal path generation. [ABSTRACT FROM AUTHOR]

This paper presents an exoskeleton mechanism designed to assist the locomotion of individuals with disabilities. The model is a walking biped mechanism developed within our research team, consisting of two identical kinematic chains driven by a single motor. The mechanism is modeled using SolidWorks for kinematic analysis and 3D printing purposes. Kinematic analysis is performed using Altair Inspire program to validate the functionality of the geometric model. Finally, 3D printing is performed to obtain a prototype of the robotic system, thus benefiting from the advantages of 3D printing technology, especially obtaining the component parts at a lower cost price compared to classical processing technology. [ABSTRACT FROM AUTHOR]

The robots with humanoid hands can take the place of humans in carrying objects and using tools efficiently in different situations. This paper presents a novel hydraulic-driven robotic hand named the WLRH-II (the second-generation wheel-legged robot humanoid hand) which bears heavy load and has strong robustness. This paper focuses on the design of humanoid hand driving and transmission mechanisms, kinematic and static analyses. First, the linkage mechanism is proposed according to the particle swarm optimization algorithm. Then, the kinematics and the statics of WLRH-II are analyzed in grasp state. In addition, the hydraulic servo control method is used to control the position of a hand through angle feedback. Finally, position tracking and load experiments are completed to verify the reasonableness and effectiveness of the control. The robotic hand can grasp objects of 30 kg with 2.85-kg self-weight. The WLRH-II has a high load/self-weight ratio of 10.55 in this paper, which is rare in similar humanoid robotic hands. [ABSTRACT FROM AUTHOR]

Abstract: Conventional mobile robots have difficulty navigating highly unstructured spaces such as caves and forests. In these environments, a highly extendable limb could be useful for deploying hooks to climb over terrain, or for reaching hard-to-access sites for sample collection. This article details a new form of a multimodal mobile robot that utilizes a novel tape spring limb named EEMMMa (elastic extending mechanism for mobility and manipulation). Its innovative U-shaped tape structure allows it to handle loads in tension as well as compression. It can also bend using mechanical multiplexing for a lightweight and compact design that is well suited for mobile robots. For mobility, the limb can extend prismatically to deploy grappling hook anchors to suspend and transport the main body, or even serve as legs. For manipulation, the limb can morph its shape to bend around or over obstacles, allowing it to retrieve distant objects or position cameras around corners. The EEMMMa-1 prototype detailed in this article successfully demonstrates climbing ladders and shelves in 1.5 body lengths per second, and can bend up to 100 deg. A simplified model of the bending kinematics is developed and analyzed. This article concludes by detailing future EEMMMa applications and theories to strengthen the model in future studies.

Mobile Edge Computing (MEC) aims at decreasing the response time and energy consumption of running mobile applications by offloading the tasks of mobile devices (MDs) to the MEC servers located at the edge of the network. The demands are multi-attribute, where the distances between MDs and access points lead to differences in required resources and transmission energy consumption. Unfortunately, the existing works have not considered both task allocation and energy consumption problems. Motivated by this, this paper considers the problem of task allocation with multi-attributes, where the problem consists of the winner determination and offloading decision problems. First, the problem is formulated as the auction-based model to provide flexible service. Then, a randomized mechanism is designed and is truthful in expectation. This drives the system into an equilibrium where no MD has incentives to increase the utility by declaring an untrue value. In addition, an approximation algorithm is proposed to minimize remote energy consumption and is a polynomial-time approximation scheme. Therefore, it achieves a tradeoff between optimality loss and time complexity. Simulation results reveal that the proposed mechanism gets the near-optimal allocation. Furthermore, compared with the baseline methods, the proposed mechanism can effectively increase social welfare and bring higher revenue to edge server providers.

IntroductionIsokinetic exercise can improve joint muscle strength and stability, making it suitable for early rehabilitation of stroke patients. However, traditional isokinetic equipment is bulky and costly, and cannot effectively avoid external environmental interference.MethodsThis paper designed a lightweight upper limb joint isokinetic rehabilitation training equipment, with a control system that includes a speed planning strategy and speed control with disturbance rejection. Based on the established human-machine kinematic closed-loop model between the equipment and the user, a dynamic evaluation method of torque at the joint level was proposed.ResultsTo validate the effectiveness of the equipment, experiments were conducted by manually applying random disturbances to the equipment operated at an isokinetic speed. The results showed that the root mean square error between the observed torque curve of the second-order linear extended state observer used in this paper and the actual disturbance curve was 0.52, and the maximum speed tracking error of the speed control algorithm was 1.27%. In fast and slow sinusoidal speed curve tracking experiments, the root mean square errors of the speed tracking results for this algorithm were 9.65 and 5.27, respectively, while the tracking errors for the PID speed control algorithm under the same environment were 19.94 and 12.11.DiscussionThe research results indicate that compared with traditional PID control method, the proposed control strategy demonstrates superior performance in achieving isokinetic control and suppressing external disturbances, thereby exhibiting significant potential in promoting upper limb rehabilitation among patients.

Peer-to-Peer (P2P) energy trading between Interconnected Micro-Grids (IMGs) presents a promising approach for enhancing the economic advantages for prosumers while mitigating supply–demand imbalances within individual Micro-Grids (MGs). This paper proposes a trustful double auction mechanism for P2P energy trading among prosumers in IMGs, structured into two distinct stages. Initially, concurrent auctions are conducted within each MG to facilitate intra-grid trading, followed by subsequent auctions facilitating inter-grid trading across IMGs. We figure out the allocation and pricing rules that satisfy the required properties in mechanism design even when the auction consists of two stages. Given that energy transactions across IMGs entail non-negligible power losses, equitable allocation of these losses among prosumers is paramount. To address this, we integrate a fair cost distribution methodology into our auction mechanism, implemented by an iterative algorithm. Rigorous analysis substantiates our proposed auction mechanism’s incentive compatibility, individual rationality, and budget balance, thereby fostering truthful and voluntary prosumer participation while averting potential market deficits. Numerical analysis underscores the efficacy of our approach, showcasing a significant improvement in P2P transactions and supply–demand balance enhancement compared to trading solely within individual MGs.