Search Results (25)

Traditionally, the determination of the Denavit–Hartenberg (DH) parameters for serial robotic manipulators is a manual process that depends on manufacturer documentation or user-defined conventions, often leading to inefficiency and ambiguity in DH frame placement and parameters. This study introduces a universal and systematic methodology for automatically deriving DH parameters directly from a robot’s zero configuration, using only the geometric relationships between consecutive joint axes. The approach was implemented in a MATLAB-based kinematics toolbox capable of computing both the classical and modified DH parameters. In addition to parameter extraction, the toolbox integrates workspace visualization, manipulability and dexterity analysis, and a slicing and alpha-shape algorithm for accurate workspace volume computation. Validation was conducted on multiple industrial robots by comparing the extracted parameters with the manufacturer data and the RoboDK models. Benchmark studies confirmed the accuracy of the volume estimation, yielding an absolute percentage error of less than 4%. While the current implementation relies on RoboDK models for verification and requires the manual tuning of the alpha-shape parameter, the toolbox provides a reproducible and extensible framework for research, education, and robot design. Full article

Much as the information generated by our fingertips is used for fine-scale grasping and manipulation, closed-loop dexterous robotic manipulation requires rich tactile information to be generated by artificial fingertip sensors. In particular, fingertip shear sensing dominates modalities such as twisting, dragging, and slipping, but there is limited research exploring soft shear predictions from an increasingly popular single-material tactile technology: electrical impedance tomography (EIT). Here, we focus on the twisting of a screwdriver as a representative shear-based task in which the signals generated by EIT hardware can be analyzed. Since EIT’s analytical reconstructions are based upon conductivity distributions, we propose and investigate five reduced-order models which relate shear-based screwdriver twisting to the conductivity maps of a robot’s single-material sensorized fingertips. We show how the physical basis of our reduced-order approach means that insights can be deduced from noisy signals during the twisting tasks, with respective torque and diameter correlations of 0.96 and 0.97 to our reduced-order parameters. Additionally, unlike traditional reconstruction techniques, all necessary FEM model signals can be precalculated with our approach, promising a route towards future high-speed closed-loop implementations. Full article

To improve the mobility of mobile robots in complex terrain environments, a novel 2-UPS&PRPU parallel mechanism is proposed, for which the parallel mechanism branched-chain decomposition and synthesis method is adopted. Based on the structural characteristics of the Hooke joint kinematic substructure, an inverse solution calculation for the mechanism is carried out, and the parameters of the simulation model are formulated to determine the workspace of the parallel mechanism. The linear velocity dexterity and minimum output carrying capacity of the parallel mechanism are analyzed, allowing the optimal parameters of the mechanism to be selected through dimension optimization, thus greatly improving the mechanism’s linear velocity dexterity and carrying capacity. The results show that the proposed parallel mechanism can satisfy the mobility requirements of mobile robots. Full article

The complex structure of the wrist joint supports the hand to complete a variety of dexterous and accurate operations in daily living, which in turn makes it vulnerable to motor injury due to stroke, sports, occupational, or traffic accidents. As a supplement to traditional medical treatment, timely and effective rehabilitation training can accelerate the recovery process of wrist motor function. The wearable rehabilitation device in this work exhibits excellent application prospects in the field of human rehabilitation training due to its inherent flexibility and safety. Inspired by the motion principle of tendons and muscles, a modular vacuum-actuated artificial muscle (VAM) is proposed, with the advantages of being lightweight and having a high contraction ratio. The VAMs are applied to the development of a wearable wrist rehabilitation device (WWRD) prototype, which can realize wrist rehabilitation training in the motion directions of extension, flexion, radial deviation, and ulnar deviation. The design concept, structural model, and motion analysis of a WWRD are introduced to provide a reference for the design and analysis of the WWRD prototype. To evaluate the performance of the WWRD, we establish the force and motion parameter models of the WWRD and carry out performance experiments. The process of wrist rehabilitation training is tested and evaluated, which indicates that the WWRD with VAMs will enhance flexibility, comfort, and safety in wrist rehabilitation training. This work is expected to promote the development of high-performance wearable wrist rehabilitation devices based on an understanding of the bionic vacuum-actuated artificial muscles. Full article

With the continuous development of modern robotics technology, in order to overcome the obstacles to the ability to complete tasks due to the fixed structure of the robot itself, to realize the reconfigurable purpose of the manipulator, it can be assembled into different degrees of freedom or configurations according to the needs of different tasks, which has the characteristics of a compact structure, high integrability, and low cost. The overall design scheme of a cable-free modular reconfigurable manipulator is proposed, and based on the target design parameters, the structural design of each module is completed, and the module library is constructed. Each module realizes rapid assembly or disassembly through a new type of docking mechanism module, which improves the flexibility and reliability of the manipulator. Meanwhile, a finite element analysis is carried out on the whole manipulator to optimize the structure that does not meet the strength and stiffness requirements. The wireless energy transmission module is integrated into the joint module to realize the cable-free design of the manipulator in the structure. The kinematic models of each module are established separately, providing a method to quickly construct the kinematics of different configurations of the manipulator, and the dexterity of the workspace is analyzed. Then, two methods, joint space planning and Cartesian space planning, are adopted to generate the corresponding motion paths and kinematic curves, which successfully verifies the reasonableness of the kinematics of the designed manipulator. Finally, combined with the results of the dynamics simulation, the corresponding dynamics curves of the end of each joint are generated to further verify the reliability of its design. It provides a new way of thinking for the research and development of highly intelligent and highly integrated manipulators. Full article

This paper proposes an underactuated dexterous hand with novel bidirectional self-locking joints (BSJs) that enable multiple fingertip motion trajectories. The BSJ design integrates a locking wheel, rack, finger side walls, and a self-holding electromagnetic actuator, combining rack-and-pinion transmission with friction self-locking principles. Building on the BSJ concept, an underactuated dexterous hand is developed. The study begins with an analysis of BSJ’s deviation angle, establishing the minimum deviation angle critical to its operation. A detailed mechanical model of a BSJ is formulated, and its parameters are quantitatively analyzed to determine a safety static friction coefficient (0.177). Five distinct finger motion modes are designed and kinematic analysis focuses on the index finger and the generation of 57 unique fingertip active motion trajectories. Experimental validation included single finger performance tests that confirmed the diversity of fingertip trajectories and the hand’s ability to withstand loading in both forward and reverse directions. Through envelope and precision grasping experiments, the dexterous hand demonstrated its adaptability and ability to grasp objects of various sizes and shapes, such as strawberries, apples, student ID cards, and water bottles. This capability underscores its potential for a wide range of applications, from prosthetic hands for rehabilitation, where precision and adaptability are key, to robotic hands in industrial automation, offering flexibility in diverse tasks. Full article

In the pursuit of developing expressive music performance models using artificial intelligence, this paper introduces DExter, a new approach leveraging diffusion probabilistic models to render Western classical piano performances. The main challenge faced in performance rendering tasks is the continuous and sequential modeling of expressive timing and dynamics over time, which is critical for capturing the evolving nuances that characterize live musical performances. In this approach, performance parameters are represented in a continuous expression space, and a diffusion model is trained to predict these continuous parameters while being conditioned on a musical score. Furthermore, DExter also enables the generation of interpretations (expressive variations of a performance) guided by perceptually meaningful features by being jointly conditioned on score and perceptual-feature representations. Consequently, we find that our model is useful for learning expressive performance, generating perceptually steered performances, and transferring performance styles. We assess the model through quantitative and qualitative analyses, focusing on specific performance metrics regarding dimensions like asynchrony and articulation, as well as through listening tests that compare generated performances with different human interpretations. The results show that DExter is able to capture the time-varying correlation of the expressive parameters, and it compares well to existing rendering models in subjectively evaluated ratings. The perceptual-feature-conditioned generation and transferring capabilities of DExter are verified via a proxy model predicting perceptual characteristics of differently steered performances. Full article

Dexterous manipulation of unknown objects performed by robots equipped with mechanical hands represents a critical challenge. The difficulties arise from the absence of a precise model of the manipulated objects, unpredictable environments, and limited sensing capabilities of the mechanical hands compared to human hands. This paper introduces a data-driven approach that provides a learning-based planner for dexterous manipulation employing an Adaptive Neuro-Fuzzy Inference System (ANFIS) fed by data obtained from an analytical manipulation planner. ANFIS captures the complex relationships between inputs and optimal manipulation parameters. Moreover, during a training phase, it is able to fine-tune itself on the basis of its experiences. The proposed planner enables a robot to interact with objects of various shapes, sizes, and material properties while providing an adaptive solution for increasing robotic dexterity. The planner is validated in a real-world environment, applying an Allegro anthropomorphic robotic hand. A link to a video of the experiment is provided in the paper. Full article

In this study, a dual-mode reconfigurable parallel ankle joint rehabilitation mechanism is proposed to meet the needs of patients in different ankle rehabilitation stages. This mechanism can switch between the 1T2R (where R represents rotation and T represents translation) and 2T1R motion modes. The screw theory and the modified G-K formula were used to analyze and verify the degree of freedom of the mechanism. The non-parasitic motion characteristics were analyzed by examining the topological structure of the mechanism. An inverse kinematics model was established using the closed-loop vector method, and the mechanism’s singularity was analyzed based on the Jacobian matrix. The Jacobian matrix and the numerical method were used to compare and analyze the workspace index, the rotational dexterity index and the load capacity performance index before and after the introduction of branched chains with actuation redundancy. A particle swarm optimization algorithm was used to optimize the geometric dimensional parameters of the mechanism. The results show that the mechanism exhibits the characteristics of a parallel mechanism without parasitic motion in the two motion modes. Using branched chains with actuation redundancy can significantly improve the rotational dexterity and load capacity performance index, without affecting the workspace index. Compared to the original mechanism, the kinematic performance of the optimized mechanism is significantly improved. It is concluded that the proposed mechanism can meet the needs of ankle joint activity training in the 1T2R motion mode and the needs of ankle joint proprioception training in the 2T1R motion mode, which can better meet the needs of patients in different rehabilitation stages. Full article

Human–machine interface technology is fundamentally constrained by the dexterity of motion decoding. Simultaneous and proportional control can greatly improve the flexibility and dexterity of smart prostheses. In this research, a new model using ensemble learning to solve the angle decoding problem is proposed. Ultimately, seven models for angle decoding from surface electromyography (sEMG) signals are designed. The kinematics of five angles of the metacarpophalangeal (MCP) joints are estimated using the sEMG recorded during functional tasks. The estimation performance was evaluated through the Pearson correlation coefficient (CC). In this research, the comprehensive model, which combines CatBoost and LightGBM, is the best model for this task, whose average CC value and RMSE are 0.897 and 7.09. The mean of the CC and the mean of the RMSE for all the test scenarios of the subjects’ dataset outperform the results of the Gaussian process model, with significant differences. Moreover, the research proposed a whole pipeline that uses ensemble learning to build a high-performance angle decoding system for the hand motion recognition task. Researchers or engineers in this field can quickly find the most suitable ensemble learning model for angle decoding through this process, with fewer parameters and fewer training data requirements than traditional deep learning models. In conclusion, the proposed ensemble learning approach has the potential for simultaneous and proportional control (SPC) of future hand prostheses. Full article

Soil physical quality (SPQ) is a limiting factor affecting crop production. However, the impact of gully erosion on the SPQ index S, defined by Dexter as the inflection point of the soil water retention curve (SWRC), remains unclear, especially when considering different latitudinal regions. This study aimed to apply Dexter’s S-theory to evaluate the distribution of index S in black soils adjacent to various gully positions and investigate its relationship with bulk density (Bd), soil organic matter (SOM), and particle percentage. Soil properties (SWRC, Bd, SOM, and particle percentage) from nine gullies in croplands in three latitudinal regions (Harbin, Hailun, and Nenjiang in Heilongjiang province) were determined at the gully edge (GE₀) and 50 m beyond the edge into the croplands (GE₅₀) at the following gully units: head, mid-upper, middle, mid-lower, tail, and conjunctions between main gully and gully branch. The S-index was calculated using parameters such as n, θ_s, and θ_r, with SWRC data fitted into the van Genuchten model. The results showed spatial variations in the S-index across latitudinal regions, with slightly higher S-values in Harbin than in Hailun and Nenjiang. The S-index also showed noticeable differences at GE₀ and GE₅₀ and at the junctions between the main gully and its branches. Approximately 51% of the samples at GE₀ and 28.2% of the samples at GE₅₀ had S-values below 0.035, which Dexter proposed as the boundary between good and poor SPQ, indicating a degradation of SPQ at the gully-surrounding areas. A decreased S-index in the gully vicinity was significantly (p < 0.05) associated with increased bulk density (1.33 vs. 1.21 g cm⁻³ for GE₀ and GE₅₀) and decreased SOM (36.80 vs. 39.36 g kg⁻¹ for GE₀ and GE₅₀). In summary, this study indicates that gully erosion affects the farmland S-index at the gully-surrounding areas through SOM and Bd. Accordingly, measures suited to the increase in the S-index of the gully-surrounding areas may be implemented to maximize the crop yield of farmlands. Full article

Continuum manipulators, with their characteristics of flexibility and dexterity, have gained significant interest in various applications across industries such as inspection, manufacturing, space exploration, and medical surgery. However, because of their inherent compliance, handling payloads may prove challenging due to shape distortion and deflection. This demonstrates the need to optimize the manipulator’s stiffness. The primary objective of this work was to show the merits of sensitivity analysis in the design of flexible surgical manipulators. Such analysis can guide important design decisions and enable the more efficient use of available resources, contributing to designing more effective prototypes. A new sensitivity analysis framework based on a multi-model and a multi-method approach was proposed to achieve this. This framework was then demonstrated by studying a tendon-driven rolling contact joint hyper-redundant manipulator for transoral laser microsurgery. In this analysis, the effects of independent design parameters on the stiffness of the manipulator were examined. Then, scaled-up 3D-printed prototypes were used to validate the accuracy of the stiffness model experimentally, which enabled us to assess the outcome of the sensitivity analysis framework. The results demonstrated that only two out of five design parameters for the considered manipulator significantly impacted the device’s performance. This information could enable the designer to efficiently allocate resources toward correctly setting these two most important parameters to achieve the desired system. Overall, the proposed analysis framework is a general tool that can be applied to any design architecture, helping to develop optimal manipulators for various applications. Full article

Functional data are being used increasingly in recent years and in many environmental sciences, such as hydrology applied to agriculture. This means that the output, instead of a scalar variable represented by a spatial map, is given by a function. Furthermore, in site-specific management, there is a need to delineate the field into management areas depending on the agricultural procedure and on the scale of application. In this paper, an approach based on multivariate geostatistics is illustrated that uses the parameters of Dexter’s water retention model and some soil properties to arrive at a multiscale delineation of an agricultural field in Iran. One hundred geo-referenced soil samples were taken and subjected to various measurements. The volumetric water contents at the different suctions were fitted to Dexter’s model. The estimated curve parameters plus the measurements of the soil variables were transformed into standardized Gaussian variables and the values transformed were subjected to geostatistical cokriging and factorial cokriging procedures. These results show that soil properties (organic carbon, bulk density, saturated hydraulic conductivity and tensile strength of soil aggregates) influence the parameters of Dexter’s model, although to different extents. The thematic maps of both soil properties and water retention curve parameters displayed a varying degree of spatial association that allowed the identification of homogeneous areas within the field. The first regionalized factors (F1) at the scales of 508 m and 3000 m made it possible to provide different delineations of the field into homogeneous areas as a function of scale, characterized by specific physical and hydraulic properties. F1 at a short and long distance could be interpreted as “porosity indicator” and “hydraulic indicator”, respectively. Such type of field delineation proves particularly useful in sustainable irrigation management. This paper emphasizes the importance of taking the spatial scale into account in precision agriculture. Full article

This paper presents a novel ankle rehabilitation (2-CRS+PU)&R hybrid mechanism, which can meet the size requirements of different adult lower limbs based on the three-movement model of the ankle. This model is related to three types of movement modes of the ankle movement, without axis offset, which can cover the ankle joint movements. The inverse and forward position/kinematics results analysis of the mechanism is established based on the closed-loop vector method and using the optimization of particle groups algorithm. Four groups of position solutions of the mechanism are obtained. The kinematics simulation is analyzed using ADAMS software. The variations of the velocity and acceleration of all limbs are stable, without any sudden changes, which can effectively ensure the safety and comfort of the ankle model end-user. The dexterity of the mechanism is analyzed based on the transport function, and the results indicate that the mechanism has an excellent transfer performance in yielding the structure parameters. Finally, the rehabilitation evaluation is conducted according to the three types of movement modes of the ankle joint. The results show that this ankle rehabilitation mechanism can provide a superior rehabilitation function. Full article

In this study, we present a package for R that is intended as a professional tool for the management and analysis of data from educational tests and useful both in high-stakes assessment programs and survey research. Focused on psychometric models based on the sum score as the scoring rule and having sufficient statistics for their parameters, dexter fully exploits the many theoretical and practical advantages of this choice: lack of unnecessary assumptions, stable and fast estimation, and powerful and sensible diagnostic techniques. It includes an easy to use data management system tailored to the structure of test data and compatible with the current paradigm of tidy data. Companion packages currently include a graphical user interface and support for multi-stage testing. Full article