Hunt Edmund R
Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.
Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom.
Front Robot AI. 2020 Mar 16;7:23. doi: 10.3389/frobt.2020.00023. eCollection 2020.
The real world is highly variable and unpredictable, and so fine-tuned robot controllers that successfully result in group-level "emergence" of swarm capabilities indoors may quickly become inadequate outside. One response to unpredictability could be greater robot complexity and cost, but this seems counter to the "swarm philosophy" of deploying (very) large numbers of simple agents. Instead, here I argue that bioinspiration in swarm robotics has considerable untapped potential in relation to the phenomenon of phenotypic plasticity: when a genotype can produce a range of distinctive changes in organismal behavior, physiology and morphology in response to different environments. This commonly arises following a natural history of variable conditions; implying the need for more diverse and hazardous simulated environments in offline, pre-deployment optimization of swarms. This will generate-indicate the need for-plasticity. Biological plasticity is sometimes irreversible; yet this characteristic remains relevant in the context of minimal swarms, where robots may become mass-producible. Plasticity can be introduced through the greater use of adaptive threshold-based behaviors; more fundamentally, it can link to emerging technologies such as smart materials, which can adapt form and function to environmental conditions. Moreover, in social animals, individual heterogeneity is increasingly recognized as functional for the group. Phenotypic plasticity can provide meaningful diversity "for free" based on early, local sensory experience, contributing toward better collective decision-making and resistance against adversarial agents, for example. Nature has already solved the challenge of resilient self-organisation in the physical realm through phenotypic plasticity: swarm engineers can follow this lead.
现实世界高度多变且不可预测,因此在室内能成功实现群体层面“涌现”出群体能力的精细调整的机器人控制器,在室外可能很快就会变得不足。应对不可预测性的一种方法可能是增加机器人的复杂性和成本,但这似乎与部署大量简单智能体的“群体理念”背道而驰。相反,我认为群体机器人技术中的生物启发在表型可塑性现象方面具有相当大的未开发潜力:当一个基因型能够根据不同环境在生物体行为、生理和形态上产生一系列独特变化时。这通常是在经历了各种不同条件的自然历史之后出现的;这意味着在群体的离线、部署前优化中需要更多样化和危险的模拟环境。这将产生——表明需要——可塑性。生物可塑性有时是不可逆的;然而,在最小化群体的背景下,这一特性仍然具有相关性,因为机器人可能会变得可大规模生产。可塑性可以通过更多地使用基于自适应阈值的行为来引入;更根本的是,它可以与智能材料等新兴技术相联系,智能材料能够使形式和功能适应环境条件。此外,在群居动物中,个体异质性越来越被认为对群体具有功能性。表型可塑性可以基于早期的局部感官体验“免费”提供有意义的多样性,例如有助于更好的集体决策和抵御对抗性智能体。自然界已经通过表型可塑性解决了物理领域中弹性自组织的挑战:群体工程师可以效仿这一做法。