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REVIEW article

Front. Robot. AI
Sec. Bio-Inspired Robotics
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1525186
This article is part of the Research Topic Exploring Burrowing in Biological and Robotic Systems View all 4 articles

Grand Challenges for Burrowing Soft Robots

Provisionally accepted
  • 1 Yale University, New Haven, United States
  • 2 University of Notre Dame, Notre Dame, Indiana, United States

The final, formatted version of the article will be published soon.

    Robotic burrowing holds promise for applications in agriculture, resource extraction, and infrastructure development, but current approaches are ineffective, inefficient, or cause significant environmental disruption. In contrast, natural burrowers penetrate substrates with minimal disturbance, providing biomechanical principles that could inspire more efficient and sustainable mechanisms. A notable feature of many natural burrowers is their reliance on soft body compositions, raising the question of whether softness contributes to their burrowing success. This review explores the role of soft materials in biological burrowing and their implications for robotic design. We examine the mechanisms that soft-bodied organisms and soft robots employ for submerging and subterranean locomotion, focusing on how softness enhances efficiency and adaptability in granular media. We analyze the gaps between the capabilities of natural burrowers and soft robotic burrowers, identify grand challenges, and propose opportunities to enhance robotic burrowing performance. By bridging biological principles with engineering innovation, this review aims to inform the development of next-generation burrowing robots capable of operating with the efficiency and efficacy seen in nature.

    Keywords: soft robotics, burrowing, bioinspiration, granular media, Soil

    Received: 08 Nov 2024; Accepted: 20 Jan 2025.

    Copyright: © 2025 Le, Yirmibesoglu, Even, Buckner, Ozkan-Aydin and Kramer-Bottiglio. 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) or licensor 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.

    * Correspondence:
    Caitlin Le, Yale University, New Haven, United States
    Sean Even, University of Notre Dame, Notre Dame, 46556, Indiana, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.