A Fast and Reliable Pick-and-Place Application with a Spherical Soft Robotic Arm: Online appendix

Zughaibi, Jasan; Hofer, Matthias; D’Andrea, Raffaello

doi:10.3929/ethz-b-000470203

Cited by 2 publications

(1 citation statement)

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“…For the given actuator configuration, it was shown in [23] that adjusting the lower pressure level allows us to control the joint stiffness, which was experimentally validated for discrete joint stiffness levels. A continuous mapping for the joint stiffness that decouples the rotational degrees of freedom from the joint stiffness was presented in [48] and proven in [54]. We refer to this strategy as the control allocation as it maps the three original actuator pressures (p A , p B , p C ) to three virtual control inputs (∆p α , ∆p β , p), where ∆p α only affects the α-direction, ∆p β only affects the β-direction and p := min{p A , p B , p C } denotes the lower actuator pressure level affecting joint stiffness (or longitudinal elongation).…”

Section: Control Allocationmentioning

confidence: 99%

Design and Control of an Inflatable Spherical Robotic Arm for Pick and Place Applications

2021

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We present an inflatable soft robotic arm made of fabric that leverages state-of-the-art manufacturing techniques, leading to a robust and reliable manipulator. Three bellow-type actuators are used to control two rotational degrees of freedom, as well as the joint stiffness that is coupled to a longitudinal elongation of the movable link used to grasp objects. The design is motivated by a safety analysis based on first principles. It shows that the interaction forces during an unexpected collision are primarily caused by the attached payload mass, but can be reduced by a lightweight design of the robot arm. A control allocation strategy is employed that simplifies the modeling and control of the robot arm and we show that a particular property of the allocation strategy ensures equal usage of the actuators and valves. The modeling and control approach systematically incorporates the effect of changing joint stiffness and the presence of a payload mass. An investigation of the valve flow capacity reveals that a proper timescale separation between the pressure and arm dynamics is only given for sufficient flow capacity. Otherwise, the applied cascaded control approach can introduce oscillatory behavior, degrading the overall control performance. A closed form feed forward strategy is derived that compensates errors induced by the longitudinal elongation of the movable link and allows the realization of different object manipulation applications. In one of the applications, the robot arm hands an object over to a human, emphasizing the safety aspect of the soft robotic system. Thereby, the intrinsic compliance of the robot arm is leveraged to detect the time when the robot should release the object.

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Section: Control Allocationmentioning

confidence: 99%