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      Fundamentals of burrowing in soft animals and robots

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          Abstract

          Creating burrows through natural soils and sediments is a problem that evolution has solved numerous times, yet burrowing locomotion is challenging for biomimetic robots. As for every type of locomotion, forward thrust must overcome resistance forces. In burrowing, these forces will depend on the sediment mechanical properties that can vary with grain size and packing density, water saturation, organic matter and depth. The burrower typically cannot change these environmental properties, but can employ common strategies to move through a range of sediments. Here we propose four challenges for burrowers to solve. First, the burrower has to create space in a solid substrate, overcoming resistance by e.g., excavation, fracture, compression, or fluidization. Second, the burrower needs to locomote into the confined space. A compliant body helps fit into the possibly irregular space, but reaching the new space requires non-rigid kinematics such as longitudinal extension through peristalsis, unbending, or eversion. Third, to generate the required thrust to overcome resistance, the burrower needs to anchor within the burrow. Anchoring can be achieved through anisotropic friction or radial expansion, or both. Fourth, the burrower must sense and navigate to adapt the burrow shape to avoid or access different parts of the environment. Our hope is that by breaking the complexity of burrowing into these component challenges, engineers will be better able to learn from biology, since animal performance tends to exceed that of their robotic counterparts. Since body size strongly affects space creation, scaling may be a limiting factor for burrowing robotics, which are typically built at larger scales. Small robots are becoming increasingly feasible, and larger robots with non-biologically-inspired anteriors (or that traverse pre-existing tunnels) can benefit from a deeper understanding of the breadth of biological solutions in current literature and to be explored by continued research.

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          Most cited references137

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          Soft robotics: Technologies and systems pushing the boundaries of robot abilities

          The proliferation of soft robotics research worldwide has brought substantial achievements in terms of principles, models, technologies, techniques, and prototypes of soft robots. Such achievements are reviewed here in terms of the abilities that they provide robots that were not possible before. An analysis of the evolution of this field shows how, after a few pioneering works in the years 2009 to 2012, breakthrough results were obtained by taking seminal technological and scientific challenges related to soft robotics from actuation and sensing to modeling and control. Further progress in soft robotics research has produced achievements that are important in terms of robot abilities-that is, from the viewpoint of what robots can do today thanks to the soft robotics approach. Abilities such as squeezing, stretching, climbing, growing, and morphing would not be possible with an approach based only on rigid links. The challenge ahead for soft robotics is to further develop the abilities for robots to grow, evolve, self-heal, develop, and biodegrade, which are the ways that robots can adapt their morphology to the environment.
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            A Resilient, Untethered Soft Robot

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              Soft Robotics

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                Author and article information

                Contributors
                Journal
                Front Robot AI
                Front Robot AI
                Front. Robot. AI
                Frontiers in Robotics and AI
                Frontiers Media S.A.
                2296-9144
                30 January 2023
                2023
                : 10
                : 1057876
                Affiliations
                [1] 1 Dauphin Island Sea Lab , Dauphin Island, AL, United States
                [2] 2 School of Marine & Environmental Sciences , University of South Alabama , Mobile, AL, United States
                [3] 3 Mechanical Engineering Department , Case Western Reserve University , Cleveland, OH, United States
                Author notes

                Edited by: Yasemin Ozkan-Aydin, University of Notre Dame, United States

                Reviewed by: Sichuan Huang, Flexiv Robotics Inc., United States

                Junliang Tao, Arizona State University, United States

                *Correspondence: Kelly M. Dorgan, kdorgan@ 123456disl.org

                This article was submitted to Bio-Inspired Robotics, a section of the journal Frontiers in Robotics and AI

                Article
                1057876
                10.3389/frobt.2023.1057876
                9923007
                36793873
                3823575a-9ea3-4a82-8a4b-d2e86190c24a
                Copyright © 2023 Dorgan and Daltorio.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 September 2022
                : 16 January 2023
                Funding
                Funded by: Office of Naval Research , doi 10.13039/100000006;
                Award ID: N00014-20-1-2377
                Funded by: National Science Foundation , doi 10.13039/100000001;
                This work was funded by ONR code 341, grant #N00014-20-1-2377 to KMD, and NSF CAREER grant 2047330 under Foundational Robotics Research to KAD.
                Categories
                Robotics and AI
                Review

                soft robotics,sediments,soils,fracture mechanics,annelids
                soft robotics, sediments, soils, fracture mechanics, annelids

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