Latest Papers

ASME Journal of Mechanisms and Robotics

  • Finite Element Method-Based Dynamic Modeling Framework for Flexible Continuum Manipulators
    on March 5, 2024 at 12:00 am

    AbstractFlexible continuum manipulators (FCMs) are gaining importance because of their maneuverability and pliability in confined and complex spaces, where rigid link manipulators underperform. However, the dynamic behavior and control of the FCM are quite challenging due to its complex nonlinear behavior. In this study, a finite element-based dynamic model framework is derived that accounts for the geometric nonlinearities and inertial effects. An experimental setup of tendon-driven FCM, consisting of a flexible backbone, is developed to validate the model. The modal analysis of the model is in agreement with the analytical solutions, with less than 10% error. The model is also validated for various loading conditions on the tip-actuated tendon-driven FCM. The steady-state tip position predictions are within 15% of the ground truth.

  • Construction and Multi-Mode Motion Analysis of Single-Degree-of-Freedom Four-Bar Multi-Mode Planar Mechanisms Based on Singular Configuration
    on March 5, 2024 at 12:00 am

    AbstractThe traditional four-bar mechanism is renowned for its simple structure, dependable performance, and wide range of applications. The single-degree-of-freedom (DOF) four-bar multi-mode planar mechanism (MMPM) is a type of four-bar mechanism that not only has the structural characteristics of the traditional four-bar mechanisms but also can achieve multiple motion modes by changing its structure. It has the advantage of performing diverse functions while conserving resources, which opens up new possibilities for research and application of the four-bar mechanism. However, due to the lack of a systematic configuration construction method, the design and application of single-DOF four-bar MMPMs are seriously limited. This paper presents a systematic method to construct a set of single-DOF four-bar MMPMs based on the loop equations and the proposed multi-mode modules (MMMs). First, depending on the loop equations, the four-bar planar mechanism containing two branches is identified by the corresponding branch graphs. Then, three kinds of MMMs are systematically proposed for the first time, helping the identified mechanism realize multiple motion modes. Subsequently, single-DOF four-bar MMPMs are constructed by replacing the specific component of the planar mechanism with the MMMs. Furthermore, the replacement rules of MMMs and the corresponding construction steps are summarized. Finally, 14 kinds of single-DOF four-bar MMPMs are listed, and the corresponding multi-mode motion analysis is discussed at the end of this paper. The proposed method is a straightforward one, which will provide great convenience for the configuration design of single-DOF four-bar MMPMs and promote the development and application of MMPMs.

  • Development of a New Cable-Driven Planar Parallel Continuum Robot Using Compound Kinematic Calibration Method
    on March 5, 2024 at 12:00 am

    AbstractThis paper presents the design, calibration, and development of a novel cable-driven planar parallel continuum robot (PCR). The PCR employs a novel drive unit, which is mainly composed of cables, guiding pulleys, and miniature linear actuators. The kinematic model of the PCR is derived based on the constant curvature assumption and the space vector method, and its workspace and singularity are analyzed. In addition, this paper adopts a novel compound kinematic calibration method, which includes the linear calibration method in the robot-specific model and the use of genetic algorithm (GA) in the robot-independent model. To verify the validity of the calibration method, the pose accuracy is assessed by providing positional points on the elliptical trajectory, and the trajectory tracking accuracy is evaluated by using circular and rectangular trajectories. The experimental results show that the static positioning accuracy is maintained at 1 mm; meanwhile, the trajectory tracking accuracy is controlled within the range of 0.9–1.4 mm. The PCR developed in this paper shows good comprehensive performance by employing the proposed novel compound kinematic calibration method.

Efficient Model-Free Calibration of a 5-Degree of Freedom Hybrid Robot

Abstract

The pose accuracy is a crucial issue that limits the application of hybrid robots. The model-free calibration instead of complex error modeling is investigated to improve the pose accuracy of a 5-degrees-of-freedom (DOF) hybrid robot efficiently. To overcome the difficult problem of model-free calibration in high-dimension joint space that the required measurement data for accurate prediction increase exponentially, a dimensionality reduction method is proposed to decompose high-dimension joint space into two low-dimension subspaces. Then the pose errors can be respectively measured in two subspaces based on the calibrated standard poses to train their corresponding pose error predicators. The standard poses ensure the measured pose errors in two subspaces do not affect each other. Thus, a merging operation obtained by kinematic analysis can finally merge the predicted pose errors of two subspaces into the complete pose error. The error predicators established by several regression methods including artificial neural network, extreme learning machine (ELM) and Twin Gaussian process regression are compared on multi aspects, and ELM stands out among them due to its outstanding prediction accuracy, good anti-noise ability, and low training data requirements. In addition, different representations of pose and pose error are adopted at different calibration stages to deal with the influence of parasitic motion of hybrid robot for the implementation of proposed calibration method. The compensation experiment is executed and the results show that position and orientation errors are reduced by 92.4% and 88.2% on average after calibration and the pose accuracy can meet application requirements.

Read More

Journal of Mechanisms and Robotics Open Issues