Latest Papers

ASME Journal of Mechanisms and Robotics

  • Dynamics of Mobile Manipulators Using Dual Quaternion Algebra
    on September 14, 2022 at 12:00 am

    AbstractThis article presents two approaches to obtain the dynamical equations of mobile manipulators using dual quaternion algebra. The first one is based on a general recursive Newton–Euler formulation and uses twists and wrenches, which are propagated through high-level algebraic operations and works for any type of joints and arbitrary parameterizations. The second approach is based on Gauss’s Principle of Least Constraint (GPLC) and includes arbitrary equality constraints. In addition to showing the connections of GPLC with Gibbs–Appell and Kane’s equations, we use it to model a nonholonomic mobile manipulator. Our current formulations are more general than their counterparts in the state of the art, although GPLC is more computationally expensive, and simulation results show that they are as accurate as the classic recursive Newton–Euler algorithm.

Performance Simulation and Energetic Analysis of TBot High-Speed Cable-Driven Parallel Robot

Abstract

Compared with serial robots, parallel robots have the advantages of high stiffness and good dynamics. By replacing the rigid limbs with cables, the cable-driven parallel robot (CDPR) is greatly simplified in structure and lightweight. We designed a high-speed CDPR tensioned by the passive rod and spring, named TBot. The robot can realize the SCARA movement as the classical Delta parallel robot. Comparison analysis of TBot and Delta is carried out to reveal the natures of the CDPRs and rigid parallel robots, identify the key issues, and promote industrial applications. Performance of both robots is analyzed with simulation under a typical Adept Motion trajectory. Results illustrate that TBot has advantages of low cost, low inertia, low energy consumption, and adjustable workspace and has great application potential. Energy consumption of TBot is discussed, and the trajectory planning is studied with the genetic algorithm to further reduce the energy consumption, considering the influence of the passive spring. Finally, on the basis of 30% less energy consumption for the Adept Motion than Delta, extra 14.3% energy is saved through the trajectory planning of TBot.

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