This paper presents a comprehensive evaluation of Particle Swarm Optimization (PSO) variants for trajectory tracking of a cable-driven continuum robot, utilizing descriptive statistical metrics along with parametric a...
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This paper presents a comprehensive evaluation of Particle Swarm Optimization (PSO) variants for trajectory tracking of a cable-driven continuum robot, utilizing descriptive statistical metrics along with parametric and non-parametric methods for performance assessment. The forward kinematic model of the robot was derived using the constant curvature approach, and the trajectory tracking problem was formulated as an optimization task. Five PSO variants, namely Standard PSO (S-PSO), Weighted PSO (W-PSO), Quantum PSO (Q-PSO), Sine-Cosine PSO (SC-PSO), and Constricted PSO (C-PSO), were reviewed and applied to two optimization scenarios: achieving a target point without considering end-tip orientation as a basic optimization problem and achieving both position and orientation as a more complex optimization problem. To evaluate their effectiveness and robustness, each algorithm was run 30 times per scenario to optimize the arc parameters necessary for tracking 500 randomly selected end-tip poses within the robot's workspace. Descriptive statistics, as well as parametric and non-parametric statistical tests, including one-way ANOVA, Kruskal-Wallis, and Dunn's post hoc test with Holm-Bonferroni correction, were used to compare the PSO variants based on tracking error, execution time, and number of iterations. The analysis showed that for simpler trajectory tracking problems, S-PSO and W-PSO were preferred, but as task complexity increased, these variants became less effective, with Q-PSO and SC-PSO performing better in more complex scenarios. Meanwhile, C-PSO consistently underperformed across all scenarios.
In this paper, an integrated accuracy enhancement method based on both the kinematic model and the data-driven Gaussian Process Regression (GPR) technique is proposed for a cable-driven continuum robot (CDCR) with a f...
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In this paper, an integrated accuracy enhancement method based on both the kinematic model and the data-driven Gaussian Process Regression (GPR) technique is proposed for a cable-driven continuum robot (CDCR) with a flexible backbone. Different from the conventional continuumrobots driven by pneumatic actuators, a segmented CDCR is developed in this work, which is a modular manipulator composed by a number of consecutive cable-driven Segments (CDSs). Based on the unique design of the backbone structure which merely allows 2-DOF bending motions, a two-variable Product-of-Exponential (POE) formula is employed to formulate the kinematic model of the CDCR. However, such an analytic kinematic model is unable to accurately describe the actual deflections of the backbone structure. Therefore, GPR is proposed to compensate the tip error of a CDCR. Compared with other machine learning methods, GPR requires less learning parameters and training data, which makes the learning process computationally efficient. To validate the effectiveness of the proposed integrated accuracy enhancement method, experiments on the actual testbed are conducted. Experimental results show that the CDCR's position and orientation errors are reduced by 68.72% and 51.74%, respectively.
In recent years, research on continuumrobots has advanced significantly to overcome the limitations of rigid-link robots that particularly suffer when working in a confined environment and have some insecure interact...
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In recent years, research on continuumrobots has advanced significantly to overcome the limitations of rigid-link robots that particularly suffer when working in a confined environment and have some insecure interaction. To address these issues, this paper proposes a design of a novel cable-driven continuum robot (CDCR) serially formed by dual-cross-module sections inspired by a fish bone-like structure. The proposed design combines multiple features of lightweight, flexibility, rigid structural stability, and asymmetric-shaped workspace. Furthermore, based on the famous Constant Curvature Kinematic Approach, the paper develops the forward and inverse kinematics of the proposed CDCR. The Forward Kinematics (FKs) are analytically developed, whereas the Inverse Kinematics (IKs) are numerically calculated. The IK of a single CDCR's section, i.e., dual-cross-module CDCR's section, is computed using polynomial functions fitting. Knowing the end-tip coordinates of each CDCR's section, which are determined using Particle Swarm Optimization algorithm, the IK of multi-section CDCR is iteratively derived using a modular and IK-based concept of a single CDCR's section. Besides, the CDCR's workspace is analyzed and compared to that with a cylindrical backbone. Finally, in order to validate the proposed approaches, simulation examples via Matlab software for point-to-point trajectory tracking in free environment, are carried out. In addition, experimental measurements are conducted using a single CDCR's section in order to evaluate the kinematic models and to analyze the design principle in terms of load capacity.
Purpose continuumrobots modeling, be it from a hard or soft class, is giving rise to several challenges compared with rigid robots. These challenges are mainly due to kinematic redundancy, dynamic nonlinearity and hi...
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Purpose continuumrobots modeling, be it from a hard or soft class, is giving rise to several challenges compared with rigid robots. These challenges are mainly due to kinematic redundancy, dynamic nonlinearity and high flexibility. This paper aims initially at designing a hard class of continuumrobots, namely, cable-driven continuum robot (CDCR) and equally at developing their kinematic and dynamic models. Design/methodology/approach First, the CDCR prototype is constructed, and its description is made. Second, kinematic models are established based on the constant curvature assumption and inextensible bending section. Third, by using the Lagrange method, the dynamic model is derived under some simplifications and based on the kinematic equations, in which the flexible backbone's elasticity modulus was identified experimentally. Finally, the static model of the CDCR is also derived based on the dynamic model. Findings Numerical examples are carried out using Matlab software to verify the static and dynamic models. Moreover, the static model is validated by comparing the simulation's results to the real measurements that have been provided with satisfactory results. Originality/value To reduce the complexity of the dynamic model's expressions and avoid the numerical singularity when the bending angle is close to zero, some simplifications have been taken, especially for the kinetic energy terms, by using the nonlinear functions approximation. Hence, the main advantage of this analytical-approximate solution is that it can be applied in the bending angle that ranges up to 2p with reasonable errors, unlike the previously proposed techniques. Furthermore, the resulting dynamic model has, to some extent, the proprieties of simplicity, accuracy and fast computation time. Ultimately, the obtained results from the simulations and real measurements demonstrate that the considered CDCR's static and dynamic models are feasible.
cable-driven continuum robots (CDCRs) with flexible backbones have been developed to perform dexterous manipulation tasks in various confined spaces due to their high flexibility and environment adaptability. A CDCR n...
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ISBN:
(纸本)9798350360875;9798350360868
cable-driven continuum robots (CDCRs) with flexible backbones have been developed to perform dexterous manipulation tasks in various confined spaces due to their high flexibility and environment adaptability. A CDCR normally consists of a number of serially-connected identical cable-drivencontinuum Joint Modules (CDCJMs). To produce large bending movements, a CDCJM often employs a parallel cable arrangement scheme, i.e., all of its driving cables are parallel to each other in its initial pose. However, such a CDCJM will suffer form the kinematics singularity in its initial pose, in which its flexible backbone will likely produce uncontrollable s-shaped deflection curves. To overcome such difficulties, this paper proposes a tilted cable arrangement scheme for the CDCJM. Considering symmetric arrangements of driving cables, a total of six tilted cable arrangement cases are investigated. Based on the structure matrices, the statics equilibrium equations are developed for the CDCJMs. To maximize the lateral force that the cable tensions of the CDCJM can sustain, the number of driving cables and the positions of cable attachment points are optimized. The simulation results indicate that the 2-2 cable arrangement is the optimal cable arrangement for the CDCJM.
A cable-driven continuum robot (CDCR) that consists of a set of identical cable-drivencontinuum Joint Modules (CDCJMs) is proposed in this paper. The CDCJMs merely produce 2-DOF bending motions by controlling driving...
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A cable-driven continuum robot (CDCR) that consists of a set of identical cable-drivencontinuum Joint Modules (CDCJMs) is proposed in this paper. The CDCJMs merely produce 2-DOF bending motions by controlling driving cable lengths. In each CDCJM, a pattern-based flexible backbone is employed as a passive compliant joint to generate 2-DOF bending deflections, which can be characterized by two joint variables, i.e., the bending direction angle and the bending angle. However, as the bending deflection is determined by not only the lengths of the driving cables but also the gravity and payload, it will be inaccurate to compute the two joint variables with its kinematic model. In this work, two stretchable capacitive sensors are employed to measure the bending shape of the flexible backbone so as to accurately determine the two joint variables. Compared with FBG-based and vision-based shape-sensing methods, the proposed method with stretchable capacitive sensors has the advantages of high sensitivity to the bending deflection of the backbone, ease of implementation, and cost effectiveness. The initial location of a stretchable sensor is generally defined by its two endpoint positions on the surface of the backbone without bending. A generic shape-sensing model, i.e., the relationship between the sensor reading and the two joint variables, is formulated based on the 2-DOF bending deflection of the backbone. To further improve the accuracy of the shape-sensing model, a calibration method is proposed to compensate for the location errors of stretchable sensors. Based on the calibrated shape-sensing model, a sliding-mode-based closed-loop control method is implemented for the CDCR. In order to verify the effectiveness of the proposed closed-loop control method, the trajectory tracking accuracy experiments of the CDCR are conducted based on a circle trajectory, in which the radius of the circle is 55mm. The average tracking errors of the CDCR measured by the Qualisys motion
cable-driven continuum robots with hyper-redundant deformable backbones show great promise in applications, such as inspection in unstructured environments, where traditional rigid robots with discrete links and joint...
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cable-driven continuum robots with hyper-redundant deformable backbones show great promise in applications, such as inspection in unstructured environments, where traditional rigid robots with discrete links and joints fail to operate. However, the motion of existing continuumrobots is still constrained by their homogeneous backbones, and limited to environments with modest geometrical complexity. In this study, inspired by highly deformable elephant trunks, we presented a modular tensegrity structure with preprogrammable stiffness for continuumrobots. Then we derived a mechanical model based on a positional formulation finite element method for predicting the configuration of the structure in different deformation scenarios. Theoretical predictions revealed that the curvature of each segment could be regulated by preprogramming their spring stiffness. Hence, our customizable design could offer an effective route for efficient robotic interactions. We further fabricated a continuumrobot consisting of 12 modules, and showcased its deformation patterns under multiple scenarios. By regulating the distribution of spring stiffness, our robot could move through channels with varying curvatures, exhibiting its potential for applications where varying curvature, and conformal and efficient interactions are needed. Leveraging the inherent intelligence, this robotic system could simplify the complexity of the required actuation and control systems.
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