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The compliance of soft actuators makes manipulation safer and simplifies control. But their high flexibility also makes sensorization challenging. From the large space of possible deformations not all are equally important. We present a method for sensorization of soft actuators that, for a given application, finds an effective layout from a set of sensors. It starts from a redundant sensor layout and iteratively reduces the number of sensors. Applying the method to the PneuFlex actuators of the RBO Hand 2, we identify a layout of four liquid metal strain sensors and one pressure sensor to predict actuator deformation in three dimensions: flexional, lateral, and twist. Finally, the layout is used to build a sensorized RBO Hand 2. It can detect passive shape adaptation while grasping and reveals failure cases during manipulation, e.g. slipping fingers while opening a door.
Wall et al. (Mon,) studied this question.