Zero-footprint eco-robotics: A new perspective on biodegradable robots

Fabian Wiesemüller, A. Miriyev, M. Kovač
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引用次数: 4

Abstract

Robots are viable candidates for automating environmental monitoring. However, potentially toxic and non-biodegradable materials comprising state-of-the-art robots may threaten vulnerable natural environments and limit robots' use in their monitoring. When expecting robotic platforms to become increasingly ubiquitous in the near future, new robot design approaches involving biodegradable and non-fossil-based materials are required to create robots with zero and near-zero environmental impact. Here we propose the material selection and application routes for material systems integrating sensing, actuation, communication, and computation. We highlight the out-standing potential of combining living cells in the design of zero-footprint eco-robots. Due to their natural responsiveness to external triggers and morphing capabilities, alone or in combination with synthetic counterparts, living cells may drastically increase the functionality of the designed robotic systems. The present paper introduces a concept of zero-footprint, transient eco-robotics and provides methods for selection of suitable materials combining structural and functional capabilities, including sensing, self-healing, and self-terminating. We suggest that these methods can build the foundation for future environmentally sustainable robotic systems, that follow the circular economy paradigm. We also emphasize the multidisciplinary nature of the zero-footprint eco-robot design, involving material scientists, biologists, and roboticists.
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零足迹生态机器人:可生物降解机器人的新视角
机器人是自动化环境监测的可行候选者。然而,由最先进的机器人组成的潜在有毒和不可生物降解的材料可能会威胁到脆弱的自然环境,并限制机器人在监测中的使用。当期望机器人平台在不久的将来变得越来越普遍时,需要使用可生物降解和非化石材料的新机器人设计方法来创造零或接近零环境影响的机器人。在此,我们提出了集传感、驱动、通信和计算为一体的材料系统的材料选择和应用路线。我们强调了将活细胞结合在零足迹生态机器人设计中的突出潜力。由于它们对外部触发和变形能力的自然反应,单独或与合成对应物结合,活细胞可能会大大增加设计的机器人系统的功能。本文介绍了零足迹、瞬态生态机器人的概念,并提供了选择合适材料的方法,结合了结构和功能能力,包括传感、自修复和自终止。我们建议这些方法可以为遵循循环经济范式的未来环境可持续机器人系统奠定基础。我们还强调零足迹生态机器人设计的多学科性质,涉及材料科学家,生物学家和机器人专家。
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