Latest Papers

ASME Journal of Mechanisms and Robotics

  • Stable Inverse Dynamics for Feedforward Control of Nonminimum-Phase Underactuated Systems
    on January 25, 2023 at 12:00 am

    AbstractAn enhanced inverse dynamics approach is here presented for feedforward control of underactuated multibody systems, such as mechanisms or robots where the number of independent actuators is smaller than the number of degrees of freedom. The method exploits the concept of partitioning the independent coordinates into actuated and unactuated ones (through a QR-decomposition) and of linearly combined output, to obtain the internal dynamics of the nonminimum-phase system and then to stabilize it through proper output redefinition. Then, the exact algebraic model of the actuated sub-system is inverted, leading to the desired control forces with just minor approximations and no need for pre-actuation. The effectiveness of the proposed approach is assessed by three numerical test cases, by comparing it with some meaningful benchmarks taken from the literature. Finally, experimental verification through an underactuated robotic arm with two degrees of freedom is performed.

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


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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