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Modular soft robots combine the strengths of two traditionally separate areas of robotics. As modular robots, they can show robustness to individual failure and reconfigurability; as soft robots, they can deform and undergo large shape changes in order to adapt to their environment, and have inherent human safety. However, for sensing and communication these robots also combine the challenges of both: they require solutions that are scalable (low cost and complexity) and efficient (low power) to enable collectives of large numbers of robots, and these solutions must also be able to interface with the high extension ratio elastic bodies of soft robots. In this work, we seek to address these challenges using acoustic signals produced by piezoelectric surface transducers that are cheap, simple, and low power, and that not only integrate with but also leverage the elastic robot skins for signal transmission. Importantly, to further increase scalability, the transducers exhibit multi-functionality made possible by a relatively flat frequency response across the audible and ultrasonic ranges. With minimal hardware, they enable directional contact-based communication, audible-range communication at a distance, and exteroceptive sensing. We demonstrate a subset of the decentralized collective behaviors that these functions make possible with multi-robot hardware implementations. The use of acoustic waves in this domain is shown to provide distinct advantages over existing solutions. 

Soft isoperimetric truss robots have demonstrated an ability to grasp and manipulate objects using the members of their structure. The compliance of the members affords large contact areas with even force distribution, allowing for successful grasping even with imprecise open-loop control. In this work we present methods of analyzing and controlling isoperimetric truss robots in the context of grasping and manipulating objects. We use a direct stiffness model to characterize the structural properties of the robot and its interactions with external objects. With this approach we can estimate grasp forces and stiffnesses with limited computation compared to higher fidelity finite elements methods, which, given the many degrees-of-freedom of truss robots, are prohibitively expensive to run on-board. In conjunction with the structural model, we build upon a literature of differential kinematics for truss robots and apply it to the task of manipulating an object within the robot’s workspace.