AbstractThis article explores a geometric and analytical approach to error modeling for a 3-DOF parallel pointing mechanism, designed for high-precision applications such as the orientation of spacecraft antennas and space telescopes. The method innovatively represents the clearances of spherical and universal joints using three-dimensional geometries. Following this, the propagation and accumulation of these clearances are modeled through a series of geometric operations. A clear expression of the complete error boundaries of the manipulator is derived. Additionally, an analytical algorithm is introduced for the first time to calculate the maximum orientation errors given a specified rotation axis. Although the simplification operation in the analytical method might result in overestimated maximums, as verified by the case studies, the method is nonetheless valuable. The reason is that a modest overestimation yields a conservative design margin, which is beneficial for engineering applications. Furthermore, it offers an effective and novel alternative for error analysis, contributing to the field’s body of knowledge.

AbstractThis article introduces a pioneering double-crank spring gravity balancer (DSGB) with a specialized spring arrangement that overcomes the spring free-length constraint observed in previous rotating-type balancers and achieves perfect static balancing. The gravitational energy associated with a ground-connected rotary link to be balanced is represented in quadratic sine form. The DSGB employs a double-crank mechanism comprising two ground-connected cranks and a cable passing through their ends, encircling one crank's pivot, and connected to a ground-connected spring. The elongation of the spring, reflecting the distance between the ends of the cranks, is formulated as a sine function, ensuring compatibility with gravitational energy through angular and geometric constraints. Two variants of the DSGB, namely constrained and unconstrained central distance DSGB, are introduced. By maintaining a constant total of gravitational and elastic energy, constraints including spring stiffness and motion compatibility with the rotary link are established. Aligning the central distance axis of the DSGB with the rotary link and ensuring motion compatibility result in a compact ground-connected in-line DSGB module. The article illustrates the viability of DSGB modules in balancing a multi-degree-of-freedom (multi-DOF) serial manipulator by proposing modifications to spring stiffness constraints and maintaining motion-compatible constraints using pseudo bases. Prototypes and experimental studies of both 1-DOF rotary link and 2-DOF manipulator with DSGBs are developed, showing torque reduction rates up to 94.8% and 97.5%, respectively, validating the DSGB's effectiveness.

AbstractSoft fingers, exemplifying embodied intelligence, offer significant advantages in robotic grasping due to their inherent adaptability to diverse object geometries and surface textures. This adaptability is driven by their physical structure, enabling intelligent grasping behavior without relying on complex control algorithms. By integrating artificial intelligence algorithms, this study enhances the inherent embodied intelligence of soft fingers to achieve embodied artificial intelligence (EAI), addressing the critical challenge of accurately predicting grasping forces and poses. We first conducted external interaction modeling and stability metric analysis for soft fingers. Then, we introduced morphology-driven models to predict grasping forces to achieve internal interaction modeling. Furthermore, based on the unique characteristics of soft fingers, we utilize PointNet to detect and adjust grasp poses from three-dimensional points in unstructured environments, achieving stable grasping for soft robotic systems. Our experiments, conducted on a FANUC robotic platform equipped with soft fingers, utilized force sensors to validate the grasping force prediction model and evaluated grasp pose prediction accuracy in a point cloud-based single-object environment, demonstrating a high success rate for both force prediction and grasping success. These advancements, achieved through the integration of artificial intelligence algorithms with soft fingers, validate the implementation of EAI in robotic systems, enhancing adaptability, precision, and efficiency in controlled environments, and laying the groundwork for future applications in dynamic and unstructured settings.

AbstractThis contribution presents an analysis of the synthesis methods of two-loop two-layer (TLTL) hybrid platforms. It proves that synthesis methods based on loop velocity analysis, in general, lead to incorrect results. Then, three TLTL hybrid platforms, where the moving platform undergoes different types of translational motions, are synthesized. Under certain conditions, these syntheses can be performed using only the velocity analysis. The synthesis of TLTL hybrid platforms with spherical and Schönflies motions is presented. The velocity analysis coupled with arguments from the Lie algebra se(3) is shown to ensure the finite mobility of the platforms and, consequently, the validity of the synthesis process.

AbstractThis article designs and implements a three-degrees-of-freedom artificial muscle bionic eye structure, aiming to simulate the motion characteristics of the human eye. Inspired by the extraocular muscles, the bionic eye’s extraocular muscles are constructed using silicone and flexible cords, and the flexible equation of the extraocular muscles is determined through tensile experiments. Based on Listing’s law, this article conducts an in-depth analysis of eye movement patterns, establishes a mathematical model for eye movements, and determines the insertion and control points of the extraocular muscles that satisfy Listing’s law. Furthermore, through forward and inverse kinematics analyses of the bionic eye system, this article proposes a mathematical relationship between the length changes of the extraocular muscles and the final pose of the eyeball, providing a theoretical foundation for precise control and trajectory planning of the bionic eye. To verify the effectiveness of the model, a prototype of the bionic eye is designed and constructed for experimentation. Experimental results demonstrate that the bionic eye system exhibits high accuracy in continuous reciprocating motions, and in the ”8”-shaped trajectory tracking experiment, the average error between the actual motion trajectory and the theoretical trajectory is only 5.07%, validating the correctness and effectiveness of the bionic eye design. This study provides an important reference for the development of artificial muscle-driven bionic eyes.