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This paper presents a novel exoskeleton robot that can be used at home to rehabilitate the index fingers of stroke-affected patients. This exoskeleton is designed as a one-degree-of-freedom four-bar mechanism able to guide the human index finger to perform a finger curl exercise motion. The proposed device is the only lateral, stand-alone mechanism built to date that can carry the weight of the human hand, thus making the user free from wearing it. The design starts by tracing the trajectory of the index finger using 'Angulus' software. 'SALAR Mechanism Synthesizer' software is used for dimensional synthesis of the four-bar mechanism. Using additive manufacturing technology, a prototype of the proposed device is developed. Static force analysis is performed to select the most appropriate actuator for producing the required torque to manipulate the fingers effectively. The kinematics of the index finger while performing a finger curl exercise is obtained. The proposed linkage mechanism can drive the index fingers of both hands. Simulation and experimental results proved the feasibility and effectiveness of the proposed design to be used for index finger rehabilitation for a wide range of users and applications by making simple minor alterations in the design. Also, a scheme for when the device can be used for rehabilitating the middle finger together with the index finger when performing flexion and extension motions is discussed. [ABSTRACT FROM AUTHOR]

As a newly developing method, tool path generation based on vector fields often requires pre-partitioning of the surface, leading to non-smooth paths at the boundaries between surface segments. To tackle this challenge, we propose a novel global tool path planning method based on vector fields. Our approach eliminates the need for pre-partitioning of the surface and incorporates considerations to achieve uniform variance of the scallop height while ensuring path smoothness. As a result, our method enables the generation of smooth paths globally while simultaneously achieving length optimality. Experimental results demonstrate the effectiveness of our proposed method, as it achieves both smoothness and length optimality compared to state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The paper considers dimensional synthesis of a path generator four-bar linkage by applying the modified Differential Evolution (DE) algorithm. During the search of the space, the DE algorithm may skip the right solution and lead to premature convergence. If the step is reduced, the search space is reduced as well, so that convergence becomes slower. Search efficiency may be achieved by including Lévy Flight in the DE algorithm. Namely, when the DE algorithm identifies the space of best solution, then a Levý Flight step is used for local search in that region, which significantly increases the exploitation capability and allows obtaining a very efficient solution of the optimization problem. The algorithm was tested with three examples of dimensional synthesis of a path generator four-bar linkage. The proposed algorithm can be very efficiently applied to solving very complex optimization problems. [ABSTRACT FROM AUTHOR]

Four-bar linkages are critical fundamental elements of many mechanical systems, and their design synthesis is often mathematically complicated with iterative numerical solutions. Analytical methods based on Fourier coefficients can circumvent these difficulties but have issues with time parameters assignment for path generation without prescribed time in previous studies. In this paper, an improved Fourier-based point-to-point combination method is presented, which generates more points by Fourier approximation and assigns the time parameters to the given points while allowing discarding solutions with order defects. This method relies on the Fourier coefficients, improving the accuracy of synthesis solutions, and simplifying the computational procedure. Time parameters are assigned directly to the given points, which avoids the complex calculations to find intersection points in the given path, eliminates combinations that would lead to solutions with order defects, and simplifies the assessment process of synthesis results. The parameters obtained by the point-to-point combination method can be used as the parameters of the input dyad, skipping the first set of design equations for faster calculation. Several examples are presented to demonstrate the advantages of the proposed synthesis method, which is easy-understanding, computationally efficient, and yields more accurate solutions than available synthesis methods. [ABSTRACT FROM AUTHOR]

This paper introduces a walking path generation method specifically developed for the Smart Cane, which is a RNA (Robotic Navigation Assistance Device) aimed at enhancing indoor navigation for visually impaired individuals. The proposed approach combines the utilization of a LIPM (Linear Inverse Pendulum Model) and LFPC (Linear Foot Placement Controller) motion primitives to generate walking paths specifically designed for visually impaired individuals. The primary objective is to generate paths that conform to human motion constraints, thereby guaranteeing an efficient and natural navigation experience. Integrating autonomous navigation framework, the Smart Cane facilitates safe and effective guidance for visually impaired participants in the indoor environments. Furthermore, comparative experiments have been conducted to validate the effectiveness of the proposed method, providing evidence of its capability to generate walking paths that conform to human motion constraints. The experiment results indicate that the proposed walking path generation method is a promising solution to enhance the navigation experience of visually impaired individuals.

This paper presents a novel exoskeleton robot that can be used at home to rehabilitate the index fingers of stroke-affected patients. This exoskeleton is designed as a one-degree-of-freedom four-bar mechanism able to guide the human index finger to perform a finger curl exercise motion. The proposed device is the only lateral, stand-alone mechanism built to date that can carry the weight of the human hand, thus making the user free from wearing it. The design starts by tracing the trajectory of the index finger using ‘Angulus’ software. ‘SALAR Mechanism Synthesizer’ software is used for dimensional synthesis of the four-bar mechanism. Using additive manufacturing technology, a prototype of the proposed device is developed. Static force analysis is performed to select the most appropriate actuator for producing the required torque to manipulate the fingers effectively. The kinematics of the index finger while performing a finger curl exercise is obtained. The proposed linkage mechanism can drive the index fingers of both hands. Simulation and experimental results proved the feasibility and effectiveness of the proposed design to be used for index finger rehabilitation for a wide range of users and applications by making simple minor alterations in the design. Also, a scheme for when the device can be used for rehabilitating the middle finger together with the index finger when performing flexion and extension motions is discussed.

Currently, pest control work using speed sprayers results in increasing numbers of safety accidents such as worker pesticide poisoning and rollover of vehicles during work. To address this, there is growing interest in autonomous driving technology for speed sprayers. To commercialize and rapidly expand the use of self-driving speed sprayers, an economically efficient self-driving speed sprayer using a minimum number of sensors is essential. This study developed an orchard passage map using location data acquired from positioning sensors to generate autonomous driving paths, without installing additional sensors. The method for creating the orchard passage map presented in this study was to create paths using location data obtained by manually driving the speed sprayer and merging them. In addition, to apply the orchard passage map when operating autonomously, a method is introduced for generating an autonomous driving path for the work start point movement path, work path, and return point movement path. [ABSTRACT FROM AUTHOR]

The construction industry is continuously evolving, seeking innovative solutions to enhance efficiency, reduce costs, and improve safety. Unmanned aerial vehicles (UAVs), commonly known as drones, have emerged as a transformative technology in the construction sector, offering numerous advantages in data collection and site management. This paper presents a novel approach for utilizing UAVs to automate the path generation of rollers, a crucial element in the construction of roads and other large-scale infrastructure projects. A UAV was used to scan the target area to create a model; the next step was to generate the path for the rollers. Traditionally, the process of determining optimal roller paths is labor-intensive and reliant on manual surveys and engineering expertise. This study proposes a streamlined workflow that harnesses UAVs equipped with computer vision technology to capture high-resolution topographical data of construction sites. This data is then processed through an algorithm created by the authors that automatically generates optimized roller paths based on several factors. [ABSTRACT FROM AUTHOR]

With the continuous expansion of the scale of electric vehicles (EV), the coupling between the distribution system and the urban transportation system is deepening. In the context of global decarbonization, it is necessary to formulate reasonable incentives to optimize the operation of coupled transportation and power systems towards an economical and low-carbon system. To achieve this goal, we propose a collaborative optimization model that considers the overall carbon emission cost of the coupled system. To respect the actual living habits of users, elastic travel needs are also considered. First, on the transportation system side, considering two main participants, electric vehicles and gasoline vehicles (GV), a game-theoretic based traffic assignment model using user equilibrium criteria is built. To reduce the computational complexity of the sub-problem in achieving the user equilibrium, an efficient path generation model is designed, which considers the charging decision and range anxiety problems of electric vehicles and the cost of carbon emissions of gasoline vehicles. Second, on the power grid side, the optimal power flow using second-order cone programming (SOCP) for power distribution systems is built, considering the cost and carbon emission of various energy sources. Third, considering the incomplete information between the coupled system, the entire model is decoupled and solved by a distributed collaborative optimization model using the alternating direction method of multipliers (ADMM) algorithm. Finally, the proposed model and solution methods are verified by comprehensive case studies. Simulation results show that the distributed collaborative optimization model can effectively reduce the emissions of the coupled system, and provide a scientific basis for the formulation of charging prices.

Path-planning research has been the key to mobile-robot-navigation technology. However, traditional path-planning algorithms have some shortcomings. To solve these problems, this paper proposes a fusion algorithm that combines the kinematical constrained A* algorithm with the Dynamic Window Approach (DWA) algorithm. The kinematical constrained A* algorithm can plan the global path, and then the DWA algorithm can plan the local path under the global path's guidance. Firstly, combined with robot kinematics, we improve the node-expansion method and heuristic-function model of the A* algorithm, which improves the search efficiency, reduces the number of path bends and lowers the computational cost so that the path generated by the A* algorithm better meets the needs of robot motion. Secondly, we optimize the trajectory-evaluation function of the DWA algorithm so that the local paths planned by the DWA algorithm are smoother and more coherent, which is easier for robot-motion execution. Finally, we extract the key nodes from the global path planned by the A* algorithm to guide the DWA algorithm for local path planning and dynamic-obstacle avoidance and to make the local path closer to the global path. Through simulation and practical experiments, the effectiveness of the fusion algorithm proposed in this paper is verified. [ABSTRACT FROM AUTHOR]

The Laser Powder Bed Fusion method is widely used in industrial additive manufacturing, which uses a laser as energy source to melt and build up powder materials. Additive process parameters such as the laser path and power, speed, layer thickness, and rotational additive strategy influence the quality of final products. In this study, in order to evaluate the build performance according to these additive process parameters during additive manufacturing, an algorithm that automatically creates a laser path based on the geometric information of the STL (stereolithography) model was developed. In addition, an algorithm that extracts section and layer information from the STL file of the sample model and automatically creates a laser beam path according to the desired additive process parameters was developed. Based on this, a program that can predict additive build performance by using commercial software Simulia Abaqus as a solver had been developed. Using the proposed algorithm and additive build prediction technology, build performance can be evaluated at the part level, and process optimization can determine additive manufacturing conditions. Numerical simulations have shown that the developed program can predict various build performances, using the cantilever model, which is widely used for extracting eigen strains for predicting part-scale build performance, as an example. The proposed program was developed to enable eigen strain prediction without the need for additional postprocessing because the variables and environment used in the actual PBF equipment can be used for the thermal-structure coupling analysis of Simulia Abaqus as it is. Therefore, by using the algorithm and the part-level build performance prediction technology that developed in this study, it will be possible to save a lot of time and money spent on experiments to determine the best additive process conditions, and it is predicted that it is possible to expand to the simulation-based prediction technology, such as digital twin, in the future. [ABSTRACT FROM AUTHOR]

Background: In recent decades, the use of compliant mechanisms has been moved from the context of precision engineering to flapping-wing micro aerial vehicles. One of the features of compliant mechanisms in the field of bio-inspired vehicles is the high speed and high frequency of flapping-wing motion that leads to the effect of the dynamic properties of the mechanism. Purpose: In this paper, the effect of the vibrational properties of a semi-constrained compliant mechanism on the mechanism's generated path is discussed. Methods: The kinematic and dynamic governing equations of the mechanism are extracted and the analytical solution for the desired path is obtained with a vibrational approach. To validate the analytical and numerical results, one of the studied cases was constructed by the smart composite manufacturing method. The experimental results were obtained using a high-speed camera and compared with numerical and analytical solutions. Results: By investigating the results, it was found that by changing the position of the compliant linkage resulting in the frequency variation of the mechanism, flapping-wing paths like peer-shape and 8-type were obtained. Conclusion: The resulting path error was low and acceptable. [ABSTRACT FROM AUTHOR]

The exact and approximate path synthesis problems require different synthesis methods, and mastering multiple design methods increases the engineers' burden. A unified drawing method can solve the synthesis problem of four and five positions in the existed studies. In this article, a novel unified synthesis method is proposed for the exact and approximate timing-path synthesis. The approximate timing-path synthesis problem is recombining into many groups of the exact timing-path synthesis. The exact timing-path synthesis formulas are derived based on the classical dyad method, while the simplified synthesis formulas are obtained by the linear elimination method with a specific order of elimination. A distance error formula is proposed to find the optimal group from all groups of solutions, where each group of solutions is the possible solution of the pre-recombination synthesis problem. Exact timing-path synthesis usually obtains several groups (12 or 2 groups, theoretically may be 0) of solutions with different kinematic properties, then the error formula is used to find the group of solutions that has the smallest rounding error. Finally, three cases test the proposed method and prove the effectiveness of the method in solving the timing-path synthesis problem by comparing the errors with the literature results. [ABSTRACT FROM AUTHOR]

In design matters, mechanisms with deformable elements are a step behind those with rigid bars, particularly if dimensional synthesis is considered a fundamental part of mechanism design. For the purposes of this work, a hybrid rigid–flexible four-bar mechanism has been chosen, the input bar being a continuum tendon of constant curvature. The coupler curves are noticeably more complex but offer more possibilities than the classical rigid four-bar counterpart. One of the objectives of this work is to completely characterize the coupler curves of this hybrid rigid–flexible mechanism, determining the number and type of circuits as well as constituent branches. Another important aim is to apply optimization techniques to the dimensional synthesis of path generation. Considerable progress in finding the best design solutions can be obtained if all the acquired knowledge about the coupler curves of this hybrid mechanism is integrated into the optimization algorithm. [ABSTRACT FROM AUTHOR]

Dimensional synthesis of mechanisms to trace given points is an important issue in mechanism and machine science. Having no exact solution makes this issue an optimization problem. This study offers an optimization approach to dimensional synthesis of planar mechanisms. Four-bar mechanisms having one Degree Of Freedom (DOF) are chosen as the configurations. The proposed method is implemented by establishing the objective functions with specified constraints and searching for the results by using an optimization algorithm. Genetic Algorithm (GA) in Optimization Toolbox-MATLABr is selected as a solver. Different types of four-bar mechanisms like crank-rocker and doublecrank including different target points are performed. Mechanisms are depicted by resulting parameters and a prepared MATLABr script plays their animations. As a result, it is proved that the mechanisms whose dimensional properties are obtained by the GA solver have a good tracing capability for the desired paths. This study has the property of being a design guide. Its application is not limited to four-bar mechanism. Planar mechanisms with different configurations can be easily synthesized by using this technique. [ABSTRACT FROM AUTHOR]

Vertically articulated industrial robots are suitable for machining purposes owing to their advantages over multi-axis machine tools, such as larger workspace, easier installation, and lower cost. However, the rigidity and positioning accuracy of industrial robots are inferior to those of machine tools, which renders it difficult to maintain the robot posture required for machining operations. This study focuses on improving the accuracy of robot machining based on posture optimization by exploiting the kinematic redundancy of a six-axis vertically articulated robot. To decrease positioning errors caused by static and dynamic external forces during machining, this study proposes a path generation method for a redundant joint that simultaneously considers the static and dynamic rigidity of the machining robot. The relationships between the static and dynamic mechanical characteristics of the machining robot and the redundant angle are illustrated using two maps: a static stiffness map and a natural frequency map. Using these two maps in the proposed path generation method, the redundant angle that can be selected for the robot posture with arbitrary mechanical characteristics is selected. Experimental results confirm that the proposed path generation method can control the priority of reducing static positioning error and vibration amplitude by changing the weight coefficients. In addition, the proposed method can improve positioning accuracy compared with conventional trajectory generation methods for redundant robots. [ABSTRACT FROM AUTHOR]

Four-bar linkages are critical fundamental elements of many mechanical systems, and their design synthesis is often mathematically complicated with iterative numerical solutions. Analytical methods based on Fourier coefficients can circumvent these difficulties but have issues with time parameters assignment for path generation without prescribed time in previous studies. In this paper, an improved Fourier-based point-to-point combination method is presented, which generates more points by Fourier approximation and assigns the time parameters to the given points while allowing discarding solutions with order defects. This method relies on the Fourier coefficients, improving the accuracy of synthesis solutions, and simplifying the computational procedure. Time parameters are assigned directly to the given points, which avoids the complex calculations to find intersection points in the given path, eliminates combinations that would lead to solutions with order defects, and simplifies the assessment process of synthesis results. The parameters obtained by the point-to-point combination method can be used as the parameters of the input dyad, skipping the first set of design equations for faster calculation. Several examples are presented to demonstrate the advantages of the proposed synthesis method, which is easy-understanding, computationally efficient, and yields more accurate solutions than available synthesis methods.

Research on autonomous driving technology is actively underway to solve the facing problems in the agricultural field. Combine harvesters used in East Asian countries, including Korea, are tracked-type vehicles. The steering control system of the tracked vehicle has different characteristics from the wheeled vehicle used in the agricultural tractor. In this paper, a dual GPS antenna-based autonomous driving system and path tracking algorithm were developed for a robot combine harvester. An α-turn-type work path generation algorithm and a path tracking algorithm were developed. The developed system and algorithm were verified through experiments using actual combine harvesters. The experiment consisted of an experiment with harvesting work and an experiment without harvesting work. In the experiment without harvesting work, an error of 0.052 m occurred during working driving and 0.207 m during turning driving. In the experiment where the harvesting work was carried out, an error of 0.038 m occurred during work driving and 0.195 m during turning driving. As a result of comparing the non-work area and driving time to the results of manual driving, the self-driving experiment with harvesting work showed an efficiency of 76.7%. [ABSTRACT FROM AUTHOR]

Path generation means generating a path or a set of paths so that the generated path meets specified properties or constraints. To our knowledge, generating a path with the performance evaluation value of the path within a given value interval has received scant attention. This paper subtly formulates the path generation problem as an optimization problem by designing a reasonable fitness function, adapts the Markov decision process with reward model into a weighted digraph by eliminating multiple edges and non-goal dead nodes, constructs the path by using a priority-based indirect coding scheme, and finally modifies the bat algorithm with heuristic to solve the optimization problem. Simulation experiments were carried out for different objective functions, population size, number of nodes, and interval ranges. Experimental results demonstrate the effectiveness and superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Currently, pest control work using speed sprayers results in increasing numbers of safety accidents such as worker pesticide poisoning and rollover of vehicles during work. To address this, there is growing interest in autonomous driving technology for speed sprayers. To commercialize and rapidly expand the use of self-driving speed sprayers, an economically efficient self-driving speed sprayer using a minimum number of sensors is essential. This study developed an orchard passage map using location data acquired from positioning sensors to generate autonomous driving paths, without installing additional sensors. The method for creating the orchard passage map presented in this study was to create paths using location data obtained by manually driving the speed sprayer and merging them. In addition, to apply the orchard passage map when operating autonomously, a method is introduced for generating an autonomous driving path for the work start point movement path, work path, and return point movement path.

Directed Energy Deposition (DED) processes are a category of Additive Manufacturing (AM) processes that can be combined with six degrees of freedom multi-axis technologies to manufacture parts with complex internal geometries without support material, while ensuring the local distance requirements. This paper provides a numerical method to compute such a path, using both a facetized file of a part and substrates locations as inputs. Topological concepts are first described to introduce the method. The algorithm is then detailed into three steps: mesh refinement, next layer points search and connection edges computing. Application to different facetized files validates the method. [ABSTRACT FROM AUTHOR]

This paper presents the performance of a teaching-learning-based optimization (TLBO) algorithm and its elite version named as an elitist teaching-learning-based optimization algorithm (ETLBO) to obtain the optimum set of design parameters for the path synthesis of a four-bar linkage. The minimization of the position error is considered as an objective function and four case studies are considered to verify the efficiency and accuracy of the TLBO and ETLBO algorithms. The synthesized mechanism is obtained for four case studies using the 2 D movable sketch method of SolidWorks. The results have shown that the performance of the TLBO and ETLBO algorithms are better or competitive to the other optimization methods considered by the previous researchers. [ABSTRACT FROM AUTHOR]

A mathematical model of the coupler points generated by the revolute-revolute-spherical-spherical (RRSS) mechanism is established. A characteristic of the projection of feature points is identified by extending preprocessing to the coupler points. Based on this finding, the 16-geometric-parameter design process is divided into three steps. In the first step, a new objective function for optimizing the linkage angle parameters is presented. In the second step, an additional objective function based on the relationship of wavelet coefficients between the mechanism elliptical phase angles and coupler angles is proposed to optimize the linkage length parameters. In the third step, the remaining geometric parameters are calculated based on the relationship between the precision points and coupler points generated by the obtained geometric parameters. Because there are fewer independent variables in each step, the dimensionality reduction synthesis method can yield design solutions with high precision in a short time. Five examples are presented to demonstrate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

Path-planning research has been the key to mobile-robot-navigation technology. However, traditional path-planning algorithms have some shortcomings. To solve these problems, this paper proposes a fusion algorithm that combines the kinematical constrained A* algorithm with the Dynamic Window Approach (DWA) algorithm. The kinematical constrained A* algorithm can plan the global path, and then the DWA algorithm can plan the local path under the global path’s guidance. Firstly, combined with robot kinematics, we improve the node-expansion method and heuristic-function model of the A* algorithm, which improves the search efficiency, reduces the number of path bends and lowers the computational cost so that the path generated by the A* algorithm better meets the needs of robot motion. Secondly, we optimize the trajectory-evaluation function of the DWA algorithm so that the local paths planned by the DWA algorithm are smoother and more coherent, which is easier for robot-motion execution. Finally, we extract the key nodes from the global path planned by the A* algorithm to guide the DWA algorithm for local path planning and dynamic-obstacle avoidance and to make the local path closer to the global path. Through simulation and practical experiments, the effectiveness of the fusion algorithm proposed in this paper is verified.

In design matters, mechanisms with deformable elements are a step behind those with rigid bars, particularly if dimensional synthesis is considered a fundamental part of mechanism design. For the purposes of this work, a hybrid rigid–flexible four-bar mechanism has been chosen, the input bar being a continuum tendon of constant curvature. The coupler curves are noticeably more complex but offer more possibilities than the classical rigid four-bar counterpart. One of the objectives of this work is to completely characterize the coupler curves of this hybrid rigid–flexible mechanism, determining the number and type of circuits as well as constituent branches. Another important aim is to apply optimization techniques to the dimensional synthesis of path generation. Considerable progress in finding the best design solutions can be obtained if all the acquired knowledge about the coupler curves of this hybrid mechanism is integrated into the optimization algorithm.

The outbreak of COVID-19 brought great inconvenience to people's daily travel. In order to provide people with a path planning scheme that takes into account both safety and travel distance, a risk aversion path planning model in urban traffic scenarios was established through reinforcement learning. We have designed a state and action space of agents in a "point-to-point" way. Moreover, we have extracted the road network model and impedance matrix through SUMO simulation, and have designed a Restricted Reinforcement Learning-Artificial Potential Field (RRL-APF) algorithm, which can optimize the Q-table initialization operation before the agent learning and the action selection strategy during learning. The greedy coefficient is dynamically adjusted through the improved greedy strategy. Finally, according to different scenarios, our algorithm is verified by the road network model and epidemic historical data in the surrounding areas of Xinfadi, Beijing, China, and comparisons are made with common Q-Learning, the Sarsa algorithm and the artificial potential field-based reinforcement learning (RLAFP) algorithm. The results indicate that our algorithm improves convergence speed by 35% on average and the travel distance is reduced by 4.3% on average, while avoiding risk areas, compared with the other three algorithms. [ABSTRACT FROM AUTHOR]

This paper introduces an integrated path tracking control strategy for autonomous vehicles. The proposed control strategy is based on a multi-input multi-output linear model predictive control (LMPC) with a fuzzy logic switching system. The designed MPC is based on Laguerre networks. The main target of the designed MPC is to produce the optimal control signals of the steering angle and the angular velocity while considering the physical constraints of the control signals and the measurements noise. Since the vehicle model is highly nonlinear and is operated over a wide range of operating points, different linearized models are obtained. The controller parameters for each linear model are designed and tuned. The gab metric analysis is used to select a number of these models to simplify the design of the proposed controller. Then, these models are combined using a fuzzy logic controller to switch between them. To test the proposed controller performance, different paths are generated using path planning algorithms. These paths simulate different vehicle maneuvers scenarios. The simulation results show that the designed tracking controller has a tracking performance on different designed paths better than that of a Linear quadratic gaussian (LQG) tracking controller, discussed in this paper. • MIMO model predictive control is designed based on Laguerre filter for autonomous vehicles. • Fuzzy system is used to smoothly switch between linearized models. • Gap-metric analysis is used to reduce the number of the linearized models. • Proposed multi-model controller perfectly tracks paths regardless their complexity. [ABSTRACT FROM AUTHOR]

Flexure-hinge compliant mechanisms have developed rapidly in precision engineering and robotics, especially in the context of micro aerial vehicles, where researchers employ such mechanisms for generating flapping-wing paths. This paper focuses on the design of a fully compliant mechanism for generating different bio-inspired 3D wing paths. A novel design algorithm was developed based on the rigid-body replacement method. The rigid-body replacement typically involves searching a rigid-body mechanism that accomplishes the desired path and converting it into a compliant mechanism by replacing the rigid joints with flexural hinges or using the Pseudo-Rigid-Body model. In the new method, the 3D mechanism was designed in two perpendicular planes. First, the main path was developed using the four-bar mechanism synthesis methods. Then, the mechanism was dynamically designed by flexural elements in the other plane. The governing dynamic equations were derived, and the main parameters were investigated. The mechanism was prototyped by the SCM (Smart Composite Manufacturing) process. For verification, the wing path was captured by a high-speed camera and compared with the analytical path. [ABSTRACT FROM AUTHOR]

Research on autonomous driving technology is actively underway to solve the facing problems in the agricultural field. Combine harvesters used in East Asian countries, including Korea, are tracked-type vehicles. The steering control system of the tracked vehicle has different characteristics from the wheeled vehicle used in the agricultural tractor. In this paper, a dual GPS antenna-based autonomous driving system and path tracking algorithm were developed for a robot combine harvester. An α-turn-type work path generation algorithm and a path tracking algorithm were developed. The developed system and algorithm were verified through experiments using actual combine harvesters. The experiment consisted of an experiment with harvesting work and an experiment without harvesting work. In the experiment without harvesting work, an error of 0.052 m occurred during working driving and 0.207 m during turning driving. In the experiment where the harvesting work was carried out, an error of 0.038 m occurred during work driving and 0.195 m during turning driving. As a result of comparing the non-work area and driving time to the results of manual driving, the self-driving experiment with harvesting work showed an efficiency of 76.7%.

Design of one-degree-of-freedom (1-DOF) mechanisms is of paramount interest. This work deals with the generation of exact regular polygonal paths by using two particular 1-DOF mechanisms. The design of two-bar and three-bar mechanisms including non-circular gears is presented and evaluated. Differences in the kinematics of both mechanisms are discussed. The three-bar mechanism allows derivable velocity and acceleration curves during the whole trajectory, including the polygon vertices, a feature that cannot be achieved with the simpler two-bar mechanism. Hence, the three-bar mechanism makes it possible to generate perfect vertices using non-circular gears. To the best of the authors' knowledge, this mechanism is the first 1-DOF mechanism with articulated links and a non-circular gear transmission that can generate exact regular polygonal paths. The proposed mechanisms can also be applied to generate two straight lines with a given angle, which is another novel contribution of this work. A prototype of the three-bar mechanism has been developed for experimental validation. • A 1-DOF mechanism that can generate exact regular polygonal paths is presented. • Solutions with two- and three-bar mechanisms are analyzed. • The mechanism can also generate two exact straight lines with a given angle. • Non-circular gears are used to generate the required non-linear transmission. [ABSTRACT FROM AUTHOR]

This paper presents a hierarchical motion planning approach based on discrete optimization method. Well-coupled longitudinal and lateral planning strategies with adaptability features are applied for better performance of on-road autonomous driving with avoidance of both static and moving obstacles. In the path planning level, the proposed method starts with a speed profile designing for the determination of longitudinal horizon, then a set of candidate paths will be constructed with lateral offsets shifting from the base reference. Cost functions considering driving comfort and energy consumption are applied to evaluate each candidate path and the optimal one will be selected as tracking reference afterwards. Re-determination of longitudinal horizon in terms of relative distance between ego vehicle and surrounding obstacles, together with update of speed profile, will be triggered for re-planning if candidate paths ahead fail the safety checking. In the path tracking level, a pure-pursuit-based tracking controller is implemented to obtain the corresponding control sequence and further smooth the trajectory of autonomous vehicle. Simulation results demonstrate the effectiveness of the proposed method and indicate its better performance in extreme traffic scenarios compared to traditional discrete optimization methods, while balancing computational burden at the same time.

Covering with plastic film in fall and planting through the film in spring is an effective drought-resistance, potato-cultivation method. To achieve proper under-plastic-film, hill-drop potato seeding, the geometry of an existing five-link planter mechanism that is driven synchronously by two cranks rotating in the same direction has been refined through bivariate plots and numerical optimization. For this purpose, novel quantitative measures of the geometry of the crunode portion of the dibber-tip path have been introduced. The prototype planter mechanism described in detail elsewhere has then been configured according to the three optimum kinematic solutions obtained, and field tests have been carried out. All three configurations satisfied the imposed agronomic requirements of potato planting through the plastic film, with one setup performing better than the other two, and then a previously reported solution obtained through manually conducted optimization. [ABSTRACT FROM AUTHOR]

Recent advancements in robots and deep learning have led to active research in human-robot interaction. However, non-physical interaction using visual devices such as laser pointers has gained less attention than physical interaction using complex robots such as humanoids. Such vision-based interaction has high potential for use in recent human-robot collaboration environments such as assembly guidance, even with a minimum amount of configuration. In this paper, we introduce a simple robotic laser pointer device that follows an arbitrary planar path and is designed to be a visual instructional aid. We also propose an image-based automatic path generation method using reinforcement learning and a sequential pattern reduction technique. However, such vision-based human-robot interaction is generally performed in a dynamic environment, and it can frequently be necessary to calibrate the devices more than once. In this paper, we avoid the need for this re-calibration process through episodic randomization learning and improved learning efficiency. In particular, contrary to previous approaches, the agent controls the curriculum difficulty in a self-directed manner to determine the optimal curriculum. To our knowledge, this is the first study of curriculum learning that incorporates an explicit learning environment control signal initiated by the agent itself. Through quantitative and qualitative analyses, we show that the proposed self-directed curriculum learning method outperforms ordinary episodic randomization and curriculum learning. We hope that the proposed method can be extended to a general reinforcement learning framework.

Routing problems play a crucial part in urban transportation network operation and management. This study addresses the problem of finding a set of non-dominated shortest paths in stochastic transportation networks. Instead of the previous practice of assuming the travel time variability to be tracked by a known probability density function, it is extracted from the existing correlation between the traffic flow and the corresponding links' time. The time horizon is divided into time intervals/slots in which the network is assumed to experience a static traffic equilibrium with different traffic conditions for each slot. Starting with Priori demand information, prior generated paths, and a chosen traffic assignment method, the proposed methodology conducts successive simulations to the network intervals. It manages to draw both links and paths probability distribution of their travel time considering the correlation among them. Then, multi-objective analysis is conducted on the generated paths to produce the Pareto-optimal set for each demand node pair in the network. Numerical studies are conducted to show the methodology efficiency and generality for any network. The expected travel time and the reliability could be drawn for each path in the network.

Wire and arc additive remanufacturing (WAAR) technology has become a new solution for hot forging dies repair and remanufacturing. In this study, a path generation method is proposed for WAAR of hot forging dies. At first, a WAAR process of the hot forging die is presented, and considering the characteristics of large welding heat input and complex 3D digital model, the hybrid path planning strategy is confirmed as an appropriate strategy for WAAR. The developed hybrid path generation method for WAAR consists of three main steps: determine the direction of the scan line; divide and fill the internal area; and connect the sub-paths. The relatively optimal scanning direction is determined by calculating the length and inclination angle of each line segment in the contour lines, which reduces the possibility of sharp angles. The internal region is divided according to the position of the selected extreme points, and the path space is adjusted to avoid the occurrence of the unfilled phenomenon. At the stage of sub-path connection, some criteria are proposed to reduce the number of sub-paths. At last, the effectiveness and robustness of the proposed method are validated through the planar deposition experiment and the WAAR process of four damaged hot forging dies. [ABSTRACT FROM AUTHOR]

Automatic guidance systems and autonomous vehicles require tested methods of path generation to ensure successful maneuvers (such as automatic trajectory correction and headland turn management). In this study, an evolution of Zakin’s kinematic modeling, as applied in the automobile industry, is proposed for an agricultural poly-articulated vehicle (representing a tractor or other type of towing vehicle with one or more towed implements attached with an articulated hitch). Geometry, vehicle ground speed, and angular steering velocity are considered in the generation of maneuvering paths. Based on the specifics of real field conditions (slope, plant residue, resistance due to soil compaction, etc.), the initial model was improved by introducing correction coefficients. An experimental setup is proposed using a tractor with two towed implements and a testing method involving point-to-point path comparison. The modeling method has potential for integrating more complex procedures (such as path generation, geolocation, and following) into the design of a maneuvering management system for agricultural machines, which can contribute to the efficiency of field operations. [ABSTRACT FROM AUTHOR]