Self-Organization, Embodiment, and BiologicallyThe following resources related to this article are available online at www.sciencemag.org

Soft robots have garnered interest for real-world applications because of their intrinsic safety embedded at the material level. These robots use deformable materials capable of shape and behavioral changes and allow conformable physical contact for manipulation. Yet, with the introduction of soft and stretchable materials to robotic systems comes a myriad of challenges for sensor integration, including multimodal sensing capable of stretching, embedment of high-resolution but large-area sensor arrays, and sensor fusion with an increasing volume of data. This Review explores the emerging confluence of e-skins and machine learning, with a focus on how roboticists can combine recent developments from the two fields to build autonomous, deployable soft robots, integrated with capabilities for informative touch and proprioception to stand up to the challenges of real-world environments.

Soft robotics is a growing area of research which utilizes the compliance and adaptability of soft structures to develop highly adaptive robotics for soft interactions. One area in which soft robotics has the ability to make significant impact is in the development of soft grippers and manipulators. With an increased requirement for automation, robotics systems are required to perform task in unstructured and not well defined environments; conditions which conventional rigid robotics are not best suited. This requires a paradigm shift in the methods and materials used to develop robots such that they can adapt to and work safely in human environments. One solution to this is soft robotics, which enables soft interactions with the surroundings while maintaining the ability to apply significant force. This review paper assesses the current materials and methods, actuation methods and sensors which are used in the development of soft manipulators. The achievements and shortcomings of recent technology in these key areas are evaluated, and this paper concludes with a discussion on the potential impacts of soft manipulators on industry and society.

Soft materials may enable the automation of tasks beyond the capacities of current robotic technology.

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It is still not known how the “rudimentary” movements of fetuses and infants are transformed into the coordinated, flexible, and adaptive movements of adults. In addressing this important issue, we consider a behavior that has been perennially viewed as a functionless by-product of a dreaming brain: the jerky limb movements called myoclonic twitches. Recent work has identified the neural mechanisms that produce twitching as well as those that convey sensory feedback from twitching limbs to the spinal cord and brain. In turn, these mechanistic insights have helped inspire new ideas about the functional roles that twitching might play in the self-organization of spinal and supraspinal sensorimotor circuits. Striking support for these ideas is coming from the field of developmental robotics: When twitches are mimicked in robot models of the musculoskeletal system, basic neural circuitry self-organizes. Mutually inspired biological and synthetic approaches promise not only to produce better robots, but also to solve fundamental problems concerning the developmental origins of sensorimotor maps in the spinal cord and brain.

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