Latest Papers

ASME Journal of Mechanisms and Robotics

  • Measurement Configuration Optimization and Kinematic Calibration of a Parallel Robot
    by Huang C, Xie F, Liu X, et al. on December 10, 2021 at 12:00 am

    AbstractThis paper presents the kinematic calibration of a four-degrees-of-freedom (4DOF) high-speed parallel robot. In order to improve the calibration effect by decreasing the influence of the unobservable disturbance variables introduced by error measurement, a measurement configuration optimization method is proposed. Configurations are iteratively selected inside the workspace by a searching algorithm, then the selection results are evaluated through an index associated with the condition number of the identification Jacobian matrix; finally, the number of optimized configurations is determined. Since the selection algorithm has been shown to be sensitive to local minima, a meta-heuristic method has been applied to decrease this sensibility. To verify the effectiveness of the algorithm and kinematic calibration, computation validations, pose error estimations, and experiments are performed. The results show that the identification accuracy and calibration effect can be significantly improved by using the optimized configurations.

Enhancing Payload Capacity With Dual-Arm Manipulation and Adaptable Mechanical Intelligence

Abstract

Individual manipulators are limited by their vertical total load capacity. This places a fundamental limit on the weight of loads that a single manipulator can move. Cooperative manipulation with two arms has the potential to increase the net weight capacity of the overall system. However, it is critical that proper load sharing takes place between the two arms. In this work, we outline a method that utilizes mechanical intelligence in the form of a whiffletree. This system enables load sharing that is robust to position deviations between the two arms. The whiffletree utilizes pneumatic tool changers which enable autonomous attachment/detachment. We outline the overall design of a whiffletree for dual-arm manipulation. We also illustrate how this type of mechanical intelligence can greatly simplify cooperative control. Lastly, we use physical experiments to illustrate enhanced load capacity. Specifically, we show how two UR5 manipulators can re-position a 7 kg load. This load would exceed the weight capacity of a single arm, and we show that the average forces on each arm remain below this level and are relatively evenly distributed.
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