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Most working scenes of industrial robots are static scenes and from a previous static scene to a current static scene is a multi-scene. Finding optimal paths with limited time is difficult for motion planning in a high-dimensional space or in multiple scenes. The low efficiency of motion planning of rapidly-exploring random tree star in high-dimensional spaces, low adaptability of global replanning to multiple scenes are addressed by proposing the local replanning based on goal dynamically-guiding rapidly-exploring random tree star (LR-GD-RRT*). The algorithm contributes to fast path tree exploration and multi-scene motion planning. For path tree exploration, sampling points heuristically generating and new nodes growth by goal dynamically-guiding are proposed to reduce the blind and ineffective searches. Moreover, dynamic adjustment of size of new node neighborhood according to density of the obstacles is proposed to search for more neighbor nodes to optimize the path and also to reduce ineffective computation to improve efficiency. For multi-scene, three steps of trimming, re-exploration, and reconnection for local replanning are proposed. For path tree exploration, simulations in 2D plane, 3D space, and the manipulator show that GD-RRT* improves convergence speed, shortens path length and search time, compared with RRT*. For multi-scene, simulations in 3D space and with the manipulator show that the local replanning of the current scene has both lower path cost and higher planning efficiency compared with the global replanning of the previous scene. Motion of the six-degree-of-freedom robot end in a real scene also verifies the effectiveness of the LR-GD-RRT*. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal control method based on adaptive dynamic programming (ADP) for manipulators with joint limitation under input saturation. The asymmetric input saturation problem is solved by introducing a smooth function, by which the saturation and nonsmooth issues of the input caused by the actuators can be handled. Joint limitation of the manipulator is transformed through a transfer function, which is incorporated into the cost function of the whole robotic system, to guarantee the joint limitation will not be violated. Meanwhile, due to the difficulty in solving Hamilton-Jacobi-Bellman (HJB) equation, the critic network is constructed utilising radial basis function neural networks (RBFNNs) to approximate the cost function. This approach effectively overcomes the curse of dimensionality problem associated with dynamic programming. Subsequently, an ADP-based optimal controller is designed for the robotic system. Lyapunov synthesis is used in the stability analysis to prove all the signals are convergent and ultimately uniformly bounded (UUB). Simulations are conducted on a planar 3-DOF manipulator to validate the effectiveness of the proposed method. The results demonstrate the improved performance and feasibility of the developed ADP-based optimal control strategy in handling joint limitations and input saturation challenges in robotic systems. [ABSTRACT FROM AUTHOR]

Pre-treatment processing technology plays a crucial role in the overall freshwater fish processing procedure, and automatic head and tail cutting stands out as a significant pre-treatment technique within the industry. The system for removing the head and tail of freshwater fish comprised a Cartesian coordinate manipulator, a fish transfer device, a control system, and an image acquisition device. In the vision system, five image segmentation methods were utilized for fish head and tail image segmentation comparison tests. These methods include U-Net (U-shaped Deep Neural Network), DeeplabV3, PSPNet (Pyramid Scene Parsing Network), FastSCNN (Fast Semantic Segmentation Network), and ICNet (Image Cascade Network), all of which were employed to evaluate their performance. Among the tested segmentation methods, the ICNet demonstrated the most excellent segmentation capability. The experimental results indicated a segmentation accuracy of 99.01%, a mean intersection over union (MIoU) of 82.50%, and an image processing time of 15.25 ms. The results showed that the fish head and tail were successfully cut off using this model for recognition with a circular knife. Consequently, the segmentation model employed in the machine vision system within this study has demonstrated successful applicability in automatically cutting the heads and tails of freshwater fish of various sizes. [ABSTRACT FROM AUTHOR]

Optimization of the machines allows you to increase their productivity and reduce the labor costs for performing individual elements of the technological cycle of their work in the forest. In this regard, the authors offer theoretical studies that take into account the peculiarities of the work of one of the most popular logging machines today, namely, a machine for collecting and forwarding logs (forwarder). The article discusses the technological features of the functioning of these machines, identifies ways to reduce the cost of collecting logs, justifies the rational width of apiaries, which allows collecting logs with a minimum number of movements between work positions. The main purpose of the study is to substantiate the mathematical dependence for determining the rational values of such interrelated parameters of the forwarder's operation as the distance between the working positions of collecting logs and the width of apiaries. The authors propose an analytical approach to solving the problem. On the basis of the standard technological scheme of the harvester's movement through the swath, geometric regularities of the trajectory of the manipulator movement, dimensional characteristics and location of the prepared logs are revealed. As a result of the work, mathematical dependencies are constructed that make it possible to determine the rational values of the desired parameters. The results can be used by research organizations in planning the production process of logging operations. The introduction of author's recommendations into production will contribute to improving the efficiency and operation of forestry equipment. [ABSTRACT FROM AUTHOR]

In order to strengthen the hovering precision of a small unmanned helicopter with a manipulator for completing a hovering operation, in this study, a double-loop control strategy of position and attitude is designed. In the position loop, a sliding mode controller is proposed. It attains high precision and strong robustness under continuous disturbance. With the manipulator continuously operating during helicopter hovering, the overall center of gravity and the moment of inertia of the system will also change. Therefore, a backstepping sliding mode controller is proposed in the attitude loop for controlling the hovering attitude of the helicopter. The high precision and strong robustness of the control system are proven. The digital simulation presents a position steady-state error of less than 2% under constant disturbance, and the hovering attitude angle fluctuation amplitude of the helicopter is less than 0.05 rad. [ABSTRACT FROM AUTHOR]

Robotic manipulators inevitably experience the impact of uncertainties and errors, such as dimensional tolerances and joint clearances. Therefore, this paper proposes a novel method based on an interval approach to evaluate the kinematic reliability of manipulators. Kinematic reliability quantifies the probability of positioning errors that fall within allowable boundaries. As a result, reliability evaluates the probability that the interval end-effector error produced by dimensional tolerances exceeds an acceptable rate. The proposed reliability index is based on the interval error that conveys an alternative approach to the kinematic reliability methods based on probabilistic frameworks reported in the literature based on probabilistic approaches. The obtained numerical results demonstrate the viability of the proposed methodology by evaluating the reliability of a serial manipulator subjected to joint clearances and a parallel manipulator with dimensional tolerances. [ABSTRACT FROM AUTHOR]

Currently, multi-posture robots have complex grasping robotic manipulators with low power density, making it difficult to miniaturize and integrate. In this paper, a multi-posture grasping manipulator actuated by shape memory alloy with different functional modules is presented. It is composed of deflection, translation, rotation and grasping modules. Based on a D-H parameter method, the end motion trajectory model is established and the end motion space is drawn. Finally, the grasping experiment of a light circular object is carried out to verify the validity of the multi-posture grasping function of the multi-module combination manipulator, which provides a choice for future intelligent robot manipulators. [ABSTRACT FROM AUTHOR]

Due to the complex growth positions of dragon fruit and the difficulty in robotic picking, this paper proposes a six degrees of freedom dragon fruit picking robot and investigates the manipulator's motion characteristics to address the adaptive motion issues of the picking manipulator. Based on the agronomic characteristics of dragon fruit cultivation, the structural design of the robot and the dimensions of its manipulator were determined. A kinematic model of the dragon fruit picking robot based on screw theory was established, and the workspace of the manipulator was analyzed using the Monte Carlo method. Furthermore, a dynamic model of the manipulator based on the Kane equation was constructed. Performance experiments under trajectory and non-trajectory planning showed that trajectory planning significantly reduced power consumption and peak torque. Specifically, Joint 3's power consumption decreased by 62.28%, and during the picking, placing, and resetting stages, the peak torque of Joint 4 under trajectory planning was 10.14 N·m, 12.57 N·m, and 16.85 N·m, respectively, compared to 12.31 N·m, 15.69 N·m, and 22.13 N·m under non-trajectory planning. This indicated that the manipulator operates with less impact and smoother motion under trajectory planning. Comparing the dynamic model simulation and actual testing, the maximum absolute error in the joint torques was −2.76 N·m, verifying the correctness of the dynamic equations. Through field picking experiments, it was verified that the machine's picking success rate was 66.25%, with an average picking time of 42.4 s per dragon fruit. The manipulator operated smoothly during each picking process. In the study, the dragon fruit picking manipulator exhibited good stability, providing the theoretical foundation and technical support for intelligent dragon fruit picking. [ABSTRACT FROM AUTHOR]

The article deals with the design of the educational model of the robot, where, in addition to kinematics, the control system of the robot and the simulation of the robot's activity in the GAZEBO environment are also addressed. Students can train different control algorithms on this model. At the same time, a graphical interface for simulating the robot's activity is also created. The control system is composed of a low-cost embedded Arduino system, which is very easy to program and create control systems. Simulations and experiments showed the correctness of the design methodology of such a robot model. [ABSTRACT FROM AUTHOR]

Feasible, smooth, and time-jerk optimal trajectory is essential for manipulators utilized in manufacturing process. A novel technique to generate trajectories in the joint space for robotic manipulators based on quintic B-spline and constrained multi-objective student psychology based optimization (CMOSPBO) is proposed in this paper. In order to obtain the optimal trajectories, two objective functions including the total travelling time and the integral of the squared jerk along the whole trajectories are considered. The whole trajectories are interpolated by quintic B-spline and then optimized by CMOSPBO, while taking into account kinematic constraints of velocity, acceleration, and jerk. CMOSPBO mainly includes improved student psychology based optimization, archive management, and an adaptive ε-constraint handling method. Lévy flights and differential mutation are adopted to enhance the global exploration capacity of the improved SPBO. The ε value is varied with iterations and feasible solutions to prevent the premature convergence of CMOSPBO. Solution density estimation corresponding to the solution distribution in decision space and objective space is proposed to increase the diversity of solutions. The experimental results show that CMOSPBO outperforms than SQP, and NSGA-II in terms of the motion efficiency and jerk. The comparison results demonstrate the effectiveness of the proposed method to generate time-jerk optimal and jerk-continuous trajectories for manipulators. [ABSTRACT FROM AUTHOR]

The underwater manipulator is a versatile tool commonly used for various underwater operations. In this study, we developed a heavy-duty hydraulic manipulator capable of operating at full ocean depth. The overall system design integrates both the mechanical structure and the electric control system. The master arm controls the slave arm by transmitting control signals to the controller and valve box. The structural design of the elbow and wrist joints has been optimized to enhance the manipulator's underwater performance and operational range. Laboratory tests demonstrated the manipulator’s excellent response consistency and tracking capability across a wide range of motion. During sea trials in the Mariana Trench, the manned submersible Fendouzhe successfully deployed the manipulator, showcasing its exceptional ability to complete complex tasks. [ABSTRACT FROM AUTHOR]

This study explores manipulator control using reinforcement learning, specifically targeting anthropomorphic gripper-equipped robots, with the objective of enhancing the robots' ability to safely exchange diverse objects with humans during human–robot interactions (HRIs). The study integrates an adaptive HRI hand for versatile grasping and incorporates image recognition for efficient object identification and precise coordinate estimation. A tailored reinforcement-learning environment enables the robot to dynamically adapt to diverse scenarios. The effectiveness of this approach is validated through simulations and real-world applications. The HRI hand's adaptability ensures seamless interactions, while image recognition enhances cognitive capabilities. The reinforcement-learning framework enables the robot to learn and refine skills, demonstrated through successful navigation and manipulation in various scenarios. The transition from simulations to real-world applications affirms the practicality of the proposed system, showcasing its robustness and potential for integration into practical robotic platforms. This study contributes to advancing intelligent and adaptable robotic systems for safe and dynamic HRIs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Donghua University (Natural Science Edition) is the property of Journal of Donghua University (Natural Science) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Featured Application: Automatic packaging of fruit grading production line. Automated packing is urgently needed in apple production. This paper proposes an improved genetic algorithm fused with an optimal parameter selection algorithm to optimize the two-posture manipulator working path of packing robots. First, the structure and working principle of the packing robot were designed. Second, the kinematics and packing paths of the two-posture manipulator were analyzed. Finally, the path optimization method for the two-posture manipulator was introduced. The method was based on the improved genetic algorithm by using a two-level coding and region crossover operator. The parameter values can be automatically determined by the optimal parameter selection algorithm. Ten repeated comparative tests show that the total packing time is 23.86 s under the working conditions of four grasping points and fourteen placing points. The optimal performance of the proposed algorithm is better than that of the traditional genetic algorithm, and the average optimization amplitudes are 14.63%, 15.42%, 16.24%, and 13.82% for 9-groove, 12-groove, 14-groove, and 16-groove trays, respectively. The proposed algorithm can effectively prevent the premature convergence problem of the traditional genetic algorithm and the optimization process instability problem, improve the range of optimization, and reduce the manipulator working time during packing. [ABSTRACT FROM AUTHOR]

Pre-treatment processing technology plays a crucial role in the overall freshwater fish processing procedure, and automatic head and tail cutting stands out as a significant pre-treatment technique within the industry. The system for removing the head and tail of freshwater fish comprised a Cartesian coordinate manipulator, a fish transfer device, a control system, and an image acquisition device. In the vision system, five image segmentation methods were utilized for fish head and tail image segmentation comparison tests. These methods include U-Net (U-shaped Deep Neural Network), DeeplabV3, PSPNet (Pyramid Scene Parsing Network), FastSCNN (Fast Semantic Segmentation Network), and ICNet (Image Cascade Network), all of which were employed to evaluate their performance. Among the tested segmentation methods, the ICNet demonstrated the most excellent segmentation capability. The experimental results indicated a segmentation accuracy of 99.01%, a mean intersection over union (MIoU) of 82.50%, and an image processing time of 15.25 ms. The results showed that the fish head and tail were successfully cut off using this model for recognition with a circular knife. Consequently, the segmentation model employed in the machine vision system within this study has demonstrated successful applicability in automatically cutting the heads and tails of freshwater fish of various sizes.

Abstract Feasible, smooth, and time-jerk optimal trajectory is essential for manipulators utilized in manufacturing process. A novel technique to generate trajectories in the joint space for robotic manipulators based on quintic B-spline and constrained multi-objective student psychology based optimization (CMOSPBO) is proposed in this paper. In order to obtain the optimal trajectories, two objective functions including the total travelling time and the integral of the squared jerk along the whole trajectories are considered. The whole trajectories are interpolated by quintic B-spline and then optimized by CMOSPBO, while taking into account kinematic constraints of velocity, acceleration, and jerk. CMOSPBO mainly includes improved student psychology based optimization, archive management, and an adaptive ε-constraint handling method. Lévy flights and differential mutation are adopted to enhance the global exploration capacity of the improved SPBO. The ε value is varied with iterations and feasible solutions to prevent the premature convergence of CMOSPBO. Solution density estimation corresponding to the solution distribution in decision space and objective space is proposed to increase the diversity of solutions. The experimental results show that CMOSPBO outperforms than SQP, and NSGA-II in terms of the motion efficiency and jerk. The comparison results demonstrate the effectiveness of the proposed method to generate time-jerk optimal and jerk-continuous trajectories for manipulators.

This paper develops a self-evolving fuzzy-based inverse dynamics controller with adaptive thresholds (SEFIDLC) for improving the control performance of uncertain nonlinear systems, which is a completely data-driven approach. The control law of the proposed approach is acquired by learning the inverse dynamics of the system from online input–output and state data. The advantages of the proposed SEFIDLC lie in the self-evolving structure and self-learning parameters that are able to adapt to the uncertainties of system dynamics. The self-evolving process involving automatic rule growing and simplification (merging and pruning) is controlled by the proposed improved adaptive thresholds. The stability and parameter convergence of the proposed controller are proved by the Lyapunov stability theory to show the tracking errors converge to a small neighborhood. Finally, the simulation and experiment results on the inverted pendulum and 3-degree-of-freedom manipulator illustrate the effectiveness of the proposed controller in handling nonlinear systems with various uncertainties. [ABSTRACT FROM AUTHOR]

A study of the boundaries of the working space of a three-link planar manipulator, specified by analytical equations, is carried out. A new geometric interpretation of these samples is proposed. On its basis, it is established that outer space consists of two-parameter volumes of eccentric and concentric circles. When transforming such environments into four-dimensional space, two types of hypersurfaces are obtained, which represent a geometric model of the manipulator's workspace. The discriminants of these hypersurfaces on the hyperplane are two two-dimensional surfaces. Both an analytical description of these surfaces and their computer models are obtained. As a result, it is established that the boundaries of the working space on the plane of the mechanism are the discriminants of such surfaces. To confirm the reliability of the results obtained, as an example, an inverse kinematics problem is solved on discriminant surfaces — the values of generalized coordinates at the boundary points of the manipulator’s workspace are determined for their given Cartesian coordinates.

The contact impact stress (CIS) between a manipulator finger and a fragile workpiece has a significant effect on clamping stability. The CIS is affected by various factors, for example, the structural form and parameters of the manipulator finger. In this paper, an optimization method combining Taguchi's method with signal-to-noise ratio (SNR) theory is proposed to reduce the CIS by optimizing the structural form and parameters of the fingers of an internally supported manipulator. The process consists of three stages. In the first stage, finite element models are built using SolidWorks, HyperMesh, and LS-DYNA software to simulate the CIS of the manipulator when gripping fragile workpieces. In the second stage, the SNR theory is applied to evaluate the effect of CIS and its fluctuations on CIS by treating the CIS and its fluctuations as signals, and changes in the structural forms and parameters of the fingers as noise. In the third stage, the optimal combination corresponding to the maximum SNR is obtained, and the degree of influence and significance level of each factor on the impact force was obtained by calculating the SNR response and variance. The simulation results indicate that the optimized structural parameters reduce the CIS by 26.85% compared to the original design. The experimental results verify the correctness of the simulation results and the effectiveness of the proposed method in reducing CIS. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Topping reduces the growing point at the top of cotton plants. This process enables the plant to allocate more energy and nutrients to fruit growth, thereby enhancing both the quantity and quality of the fruit. Current cotton-topping machinery often leads to over-topping, which can affect crop yield and quality. Manual topping is effective in controlling over-topping due to its adherence to agronomic requirements, but it is labor-intensive. This study integrated principles from biology (bionics) to design a manipulator that mimics the action of hand pinching during manual topping. Screening grids of different sizes were designed based on a statistical analysis of the biological parameters of cotton tops to optimize the topping process. A disc cam mechanism was developed to enable the automatic opening and closing of the manipulator. From the results, it was evident that the spring tension must exceed 81.5 N to properly cut the cotton stem near the top. The spacing of the screening grid (40 mm) and the position of the topping manipulator (less than 50 mm) were optimized based on experimental results. Performance testing showed promising results with a 100% topping rate. This study not only identified the challenges with current cotton-topping methods but also proposed a bionics-inspired solution; a bionic manipulator equipped with a screening grid was proposed to achieve high accuracy in cotton topping, which significantly reduced over-topping rates to 6.67%. These findings are crucial for advancing agricultural technology and improving efficiency in cotton cultivation. [ABSTRACT FROM AUTHOR]

Background: Since the advent of laparoscopic hysterectomy, several studies have described artefacts, such as vascular pseudoinvasion, constituting potential pitfalls in the histological evaluation of these specimens. The use of an intrauterine manipulator is often suggested as the factor creating these artefacts. Objectives: To describe possible artefacts, such as vascular pseudoinvasion, myometrial clefts, and tumor cells in the lumen of the cervix, on the serosa, and in the tubal lumen, and to correlate them with clinical and pathological characteristics. Material and Methods: This is a retrospective monocentric study of 60 patients having been treated for benign (n = 27, 45%) or malignant (n = 33, 55%) uterine pathologies. Results: Vascular pseudoinvasion was found in 13 (22%) adenocarcinomas and in one (2%) benign uterine pathology. Clefts within the myometrium were observed in 16 (27%) uteri. Cells in the tubal lumen were observed in six (10%) hysterectomies. True vascular emboli were not correlated with the use of an intrauterine manipulator (p = 0.47) or the type of surgery (p = 0.21). Vascular pseudoinvasion was correlated with the presence of tumor cells in the lumen of the cervix (p = 0.013) and the presence of clefts in the myometrium (p < 0.001), but not with the other factors studied. Conclusions: Overall, in our series, we did not observe any statistical association between the use of an intrauterine manipulator and the presence of true emboli or vascular pseudoinvasion during hysterectomy in women with malignant or benign uterine pathologies. Vascular pseudoinvasion was also associated with the presence of other artefacts. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a practical discrete-time control method with adaptive image feature prediction for the image-based visual servoing (IBVS) scheme is presented. In the discrete-time IBVS inner-loop/outer-loop control architecture, the time delay caused by image capture and computation is noticed. Considering the dynamic characteristics of a 6-DOF manipulator velocity input system, we propose a linear dynamic model to describe the motion of a robot end effector. Furthermore, for better estimation of image features and smoothing of the robot's velocity input, we propose an adaptive image feature prediction method that employs past image feature data and real robot velocity data to adopt the prediction parameters. The experimental results on a 6-DOF robotic arm demonstrate that the proposed method can ensure system stability and accelerate system convergence. [ABSTRACT FROM AUTHOR]

Coal is one of the important sources to meet the global energy demand. The intelligent treatment of coal gangue is of great significance to environmental protection and resource recycling. In the treatment of gangue, the use of manipulator sorting alone faces the challenge of being difficult to adapt to the increasing sorting intensity and high cost of use. In this study, we propose a hybrid sorting system that combines pneumatic separation and manipulator sorting to address the limitations of pneumatic separation sorting and manipulator. We design a task assignment algorithm based on genetic algorithms to realize their collaborative work for optimal overall sorting efficiency in a sequence of gangue. Experimental results demonstrate that the collaborative sorting system, incorporating both manipulator and high-pressure pneumatic separation, outperforms the single pneumatic separation sorting system with an average increase in sorting efficiency of 20.66%. Furthermore, the collaborative system increased sorting efficiency by up to 76.09% compared to single manipulator sorting. These findings validate the effectiveness of our proposed approach in achieving efficient sorting of coal gangue. [ABSTRACT FROM AUTHOR]

The underactuated manipulator has the advantages of simple structure, low cost, easy control and strong adaptive ability. However, the underactuated manipulator relies on mechanical limit and spring constraint to complete the grasp, resulting in poor grasping stability and inability to output greater fingertip grasping forces. Accordingly, a new underactuated three‑finger manipulator with fingertip self‑locking is proposed. The distal knuckle and middle knuckle can self‑lock when grasping, which increases the grasping stability. At the same time, the D-H kinematic model of the single finger is established, the working space of the manipulator is analyzed by MATLAB, the finger is analyzed by statics, the manipulator is simulated by ADAMS software, and finally the grasping test is carried out. The results show that the self‑locking manipulator can output greater grasping forces. Thus, the rationality and feasibility of the structure of the self‑locking manipulator are verified. [ABSTRACT FROM AUTHOR]

It is worthwhile to calculate the execution cost of a manipulator for selecting a planning algorithm to generate trajectories, especially for an agricultural robot. Although there are various off-the-shelf trajectory planning methods, such as pursuing the shortest stroke or the smallest time cost, they often do not consider factors synthetically. This paper uses the state-of-the-art Python version of the Robotics Toolbox for manipulator trajectory planning instead of the traditional D–H method. We propose a cost function with mass, iteration, and residual to assess the effort of a manipulator. We realized three inverse kinematics methods (NR, GN, and LM with variants) and verified our cost function's feasibility and effectiveness. Furthermore, we compared it with state-of-the-art methods such as Double A* and MoveIt. Results show that our method is valid and stable. Moreover, we applied LM (Chan λ = 0.1) in mobile operation on our agricultural robot platform. [ABSTRACT FROM AUTHOR]

This paper proposes a novel neural network-based control algorithm with fixed-time performance constraints for manipulator systems in workspaces. The algorithm efficiently controls the manipulator's trajectory tracking by tuning a preset performance function, thereby optimizing both speed and accuracy within a fixed timeframe. Initially, a tangent-type error transformation, applied through homogeneous embryonic transformation, ensures rapid convergence of tracking errors to a specific region. Subsequently, integrating a predetermined control strategy into the fixed-time stability framework ensures the system's state reaches a defined boundary within a finite period. Lastly, neural networks are employed to approximate dynamic parameters and adjust the controller, achieving optimal parameter approximation and significantly enhancing trajectory tracking robustness. Simulation analyses and comparisons confirm the controller's effectiveness and superiority in enhancing both the transient and steady-state performance of the control system. [ABSTRACT FROM AUTHOR]

Origami structures have made significant contributions to the field of robotics, offering various advantages. One such advantage is their ability to conserve space by transforming the structure into a compact form. Additionally, many origami structures can be fabricated in a flat state to simplify manufacturing, giving them the potential for large-scale and cost-effective production. Rotational joints play a crucial role in the construction of robotic systems, yet origami rotational joints can suffer from a limited range of motion. We previously theoretically proposed the Self-Lock Joint to address this issue, but it is only partially flat-foldable. This paper presents a novel approach to the 3D printing of modular origami joints, such as the Self-Lock Joint, using 3D-printed plates joined with a fabric layer. The compliance of the fabric can improve the joints semi flat-foldability or even enable it to achieve complete flat-foldability. Furthermore, the rotational motion of the joint is enhanced, allowing for close to 360 degrees of rotational movement. We assess the physical properties of the joint under both loaded and unloaded conditions in order to identify design trade-offs in the physical properties of the joints. Moreover, as a proof of concept, we construct and demonstrate manipulators utilizing these joints. The increase in rotational movement enabled by this fabrication method, coupled with the compliant joints flat-foldability and modular nature, make it a promising candidate for use in a wide range of applications.

Robot is an indispensable technology within the context of the Industrial 4.0 revolution, providing a wide range of applications in industry. The stability of a robot's manipulator is contingent upon its associated manipulator settings, hence influencing its overall quality. The assessment of stability has been examined in prior studies using a limited set of manipulator parameters, leading to a deficient comprehension of this phenomenon. In this study, a mathematical model of a flexible six-link manipulator is formulated using Lagrangian mechanics and various parameters. An innovative mathematical framework is developed to establish a correlation between stability and the motor acceleration and moment of inertia for the Universal Robot (UR5). Furthermore, extensive research has been conducted to examine the correlation between stiffness, damping, and deflection in the context of stability. In spite of this, fuzzy logic inference methods are employed to ascertain the relative significance of stiffness, damping, and deflection with regards to stability. Mathematical approaches are employed to validate the numerical values of several manipulator parameters. The findings of the study demonstrate that there is a positive correlation between motor acceleration and stability, indicating that as motor acceleration grows, stability also increases. Conversely, there is a negative correlation between stability and moment of inertia, suggesting that stability reduces as moment of inertia increases. In the case of stiffness, damping, and deflection, stiffness is the most important factor. When stiffness is high, stability is also high. However, when stiffness is minimal, stability is low. The implications of these findings are expected to have a positive impact on enhancing industrial productivity.

Background: Preserving the integrity of the endometrial cavity is crucial, particularly for preserving fertility during laparoscopic myomectomy (LM). This study aimed to compare the uterine breaching rate and clinical outcomes of LM performed with and without a uterine manipulator. Methods: Data from women who underwent LM at our hospital between January 2020 and June 2023 were retrospectively analyzed. The primary outcomes included endometrial cavity breaching rate, conversion rate, abdominal port count, operative time, hospitalization duration, and blood loss. The secondary outcomes included adverse events such as postoperative anemia and emphysema. Results: We analyzed the data from 50 participants, comparing those with (n=30) and without (n=20) manipulators. No significant differences were observed in age, body mass index, surgical time, hospitalization, blood loss, or hemoglobin drop. However, the incidence of endometrial cavity breach was higher in the manipulator group (p=0.007). The manipulator group required fewer abdominal ports (p

Abstract This study presents strategies for the three fundamental origami operations of grasping, bending, and folding using a novel robot hand and simple motions. These operations are executed using a simple geometric model and without any visual feedback or physical modeling not to restrict the motions. With a few applications in the field of paper manipulation, the electroadhesion technology is employed to perform single hand grasping. Bending is realized by a single hand utilizing the elasticity of origami and friction. Folding is performed by holding an origami with more than two points to fix it at any moment for preciseness. In addition to the design of hardware and motions, operations are demonstrated with general criteria for the crease precision evaluation.

This study presents strategies for the three fundamental origami operations of grasping, bending, and folding using a novel robot hand and simple motions. These operations are executed using a simple geometric model and without any visual feedback or physical modeling not to restrict the motions. With a few applications in the field of paper manipulation, the electroadhesion technology is employed to perform single hand grasping. Bending is realized by a single hand utilizing the elasticity of origami and friction. Folding is performed by holding an origami with more than two points to fix it at any moment for preciseness. In addition to the design of hardware and motions, operations are demonstrated with general criteria for the crease precision evaluation. [ABSTRACT FROM AUTHOR]

In response to the trajectory tracking control problem of manipulators under measurement disturbances, a novel multi-input multi-output discrete integral terminal sliding mode control scheme is proposed. Initially, this scheme establishes a dynamic model of a two-joint manipulator based on the Lagrangian dynamics analysis method. Subsequently, a discrete integral terminal sliding mode control law based on the dynamic model of the two joints is designed, incorporating delayed estimation of unknown disturbances and discretization errors in the manipulator system. To enhance the trajectory tracking accuracy of the control scheme and suppress the impact of sliding mode chattering on the manipulator system, an adaptive switching term is introduced into the discrete integral terminal sliding mode control law. The paper derives an adaptive discrete integral terminal sliding mode control scheme and provides stability proof for the proposed approach. Simulation experiments are conducted to compare the proposed adaptive discrete integral terminal sliding mode control scheme with classical discrete sliding mode control schemes and discrete integral terminal sliding mode control schemes. The simulation results demonstrate that the designed adaptive discrete integral terminal sliding mode control scheme maintains trajectory tracking errors within 0.004 radians for each joint of the manipulator, with minimal changes in control torque for each joint. The absolute integral of the control torque variations is calculated at 5.85 × 10 3 , which is lower than other control schemes, thereby validating the effectiveness and superiority of the proposed approach. [ABSTRACT FROM AUTHOR]