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We present a self-contained, soft robotic hand composed of soft pneumaticactuator modules that are equipped with strain and pressure sensing. We showhow this data can be used to discern whether a grasp was successful.Co-locating sensing and embedded computation with the actuators greatlysimplifies control and system integration. Equipped with a small pump, the handis self-contained and needs only power and data supplied by a single USBconnection to a PC. We demonstrate its function by grasping a variety ofobjects ranging from very small to large and heavy objects weighing more thanthe hand itself. The presented system nicely illustrates the advantages of softrobotics: low cost, low weight, and intrinsic compliance. We exploitmorphological computation to simplify control, which allows successful graspingvia underactuation. Grasping indeed relies on morphological computation atmultiple levels, ranging from the geometry of the actuator which determines theactuator's kinematics, embedded strain sensors to measure curvature, tomaximizing contact area and applied force during grasping. Morphologicalcomputation reaches its limitations, however, when objects are too bulky toself-align with the gripper or when the state of grasping is of interest. Wetherefore argue that efficient and reliable grasping also requires not onlyintrinsic compliance, but also embedded sensing and computation. In particular,we show how embedded sensing can be used to detect successful grasps and varythe force exerted onto an object based on local feedback, which is not possibleusing morphological computation alone.

Morphological and Embedded Computation in a Self-contained Soft Robotic Hand