Latest Papers

ASME Journal of Mechanisms and Robotics

  • An Improved Dual Quaternion Dynamic Movement Primitives-Based Algorithm for Robot-Agnostic Learning and Execution of Throwing Tasks
    on May 9, 2025 at 12:00 am

    AbstractInspired by human nature, roboticists have conceived robots as tools meant to be flexible, capable of performing a wide variety of tasks. Learning from demonstration methods allow us to “teach” robots the way we would perform tasks, in a versatile and adaptive manner. Dynamic movement primitives (DMP) aims for learning complex behaviors in such a way, representing tasks as stable, well-understood dynamical systems. By modeling movements over the SE(3) group, modeled primitives can be generalized for any robotic manipulator capable of full end-effector 3D movement. In this article, we present a robot-agnostic formulation of discrete DMP based on the dual quaternion algebra, oriented to modeling throwing movements. We consider adapted initial and final poses and velocities, all computed from a projectile kinematic model and from the goal at which the projectile is aimed. Experimental demonstrations are carried out in both a simulated and a real environment. Results support the effectiveness of the improved method formulation.

  • Chained Timoshenko Beam Constraint Model With Applications in Large Deflection Analysis of Compliant Mechanism
    on May 9, 2025 at 12:00 am

    AbstractAccurately analyzing the large deformation behaviors of compliant mechanisms has always been a significant challenge in the design process. The classical Euler–Bernoulli beam theory serves as the primary theoretical basis for the large deformation analysis of compliant mechanisms. However, neglecting shear effects may reduce the accuracy of modeling compliant mechanisms. Inspired by the beam constraint model, this study takes a step further to develop a Timoshenko beam constraint model (TBCM) for initially curved beams to capture intermediate-range deflections under beam-end loading conditions. On this basis, the chained Timoshenko beam constraint model (CTBCM) is proposed for large deformation analysis and kinetostatic modeling of compliant mechanisms. The accuracy and feasibility of the proposed TBCM and CTBCM have been validated through modeling and analysis of curved beam mechanisms. Results indicate that TBCM and CTBCM are more accurate compared to the Euler beam constraint model (EBCM) and the chained Euler beam constraint model (CEBCM). Additionally, CTBCM has been found to offer computational advantages, as it requires fewer discrete elements to achieve convergence.

Autonomous Docking of Hybrid-Wheeled Modular Robots With an Integrated Active Genderless Docking Mechanism

Abstract

This paper presents a self-reconfigurable modular robot with an integrated two degrees-of-freedom (DOF) active docking mechanism. Active docking in modular robotic systems has received a lot of interest recently as it allows small versatile robotic systems to coalesce and achieve the structural benefits of large systems. This feature enables reconfigurable modular robotic systems to bridge the gap between small agile systems and larger robotic systems. The proposed self-reconfigurable mobile robot design exhibits dual mobility using a tracked drive for longitudinal locomotion and a wheeled drive for lateral locomotion. The 2-DOF docking interface allows for efficient docking while tolerating misalignments. To aid autonomous docking, visual marker-based tracking is used to detect and re-position the source robot relative to the target robot. The tracked features are then used in Image-Based Visual Servoing to bring the robots close enough for the docking procedure. The hybrid-tracking algorithm allows eliminating external pixelated noise in the image plane resulting in higher tracking accuracy along with faster frame update on a low-cost onboard computational device. This paper presents the overall mechanical design and the integration details of the modular robotic module with the docking mechanism. An overview of the autonomous tracking and docking algorithm is presented along with a proof-of-concept real-world demonstration of autonomous docking and self-reconfigurability. Experimental results to validate the robustness of the proposed tracking method, as well as the reliability of the autonomous docking procedure, are also presented.
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