Latest Papers

ASME Journal of Mechanisms and Robotics

  • Investigation on a Class of 2D Profile Amplified Stroke Dielectric Elastomer Actuators
    on September 24, 2024 at 12:00 am

    AbstractDielectric elastomer actuators (DEAs) have been widely studied in soft robotics due to their muscle-like movements. Linear DEAs are typically tensioned using compression springs with positive stiffness or weights directly attached to the flexible film of the DEA. In this paper, a novel class of 2D profile linear DEAs (butterfly- and X-shaped linear DEAs) with compact structure is introduced, which, employing negative-stiffness mechanisms, can largely increase the stroke of the actuators. Then, a dynamic model of the proposed amplified-stroke linear DEAs (ASL-DEAs) is developed and used to predict the actuator stroke. The fabrication process of linear DEAs is presented. This, using compliant joints, 3D-printed links, and dielectric elastomer, allows for rapid and affordable production. The experimental validation of the butterfly- and X-shaped linear DEAs proved capable of increasing the stroke up to 32.7% and 24.0%, respectively, compared with the conventional design employing springs and constant weights. Finally, the dynamic model is validated against the experimental data of stroke amplitude and output force; errors smaller than 10.5% for a large stroke amplitude (60% of maximum stroke) and 10.5% on the output force are observed.

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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