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.

Zero Moment Control for Lead-Through Teach Programming and Process Monitoring of a Collaborative Welding Robot

Abstract

Robots are commonly used for automated welding in many industries such as automotive manufacturing. The complexity and time required for programming present an obstacle in using robotic automation in welding or other tasks for small to medium enterprises that lack resources for training or expertise in traditional robot programming strategies. It also dictates a high level of repeated parts to offset the cost of weld programming. Collaborative robots or Cobots are robots designed for more collaborative operations with humans. Cobots permit new methods of task instruction (programming) through a direct interaction between the operator and the robot. This paper presents a model and model calibration strategy for collaborative robots to aid in teaching and monitoring welding tasks. The method makes use of a torque estimation model based on robot momentum to create an observer to evaluate external forces. The torque observer is used to characterize the friction that exists within the robot joints. These data are used to define the parameters of a friction model that combines static, Coulomb, and viscous friction properties with a sigmoid function to represent a transition between motion states. With an updated friction model, the torque observer is then used for collaborative robotic welding, first to provide a mode in which the robot can be taught weld paths through physical lead through and second a mode to monitor the weld process for expected motion/force characteristics. The method is demonstrated on a commercial robot.
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