将身体与大脑协同设计,让智能体更适应环境
Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges
- 联合优化智能体形态与控制策略,打破传统分离设计
- 构建四类协同设计框架,覆盖从静态到开放的全场景
- 适合机器人、虚拟角色等需要强适应性的研究者参考
生物的脑体协同进化使动物能在环境中发展出复杂行为。受此启发,具身协同设计(ECD)作为一种变革性范式,通过联合优化智能体的形态与控制器,而非孤立设计控制,推动了从虚拟生物到物理机器人的智能体发展。该方法增强了与环境的交互能力,提升了任务鲁棒性。本文系统综述了近年ECD进展:首先形式化定义ECD并定位其在相关领域的地位;提出分层分类体系——底层将智能体设计拆解为控制脑、身体形态和任务环境三要素,上层整合为四类框架:双层、单层、生成式和开放式;据此综合分析百余篇研究。进一步梳理了模拟与真实场景中的代表性基准、数据集与应用。最后识别关键挑战,并提出未来研究方向。相关项目已开源:https://github.com/Yuxing-Wang-THU/SurveyBrainBody。
原文摘要 · Abstract (English)
Brain-body co-evolution enables animals to develop complex behaviors in their environments. Inspired by this biological synergy, embodied co-design (ECD) has emerged as a transformative paradigm for creating intelligent agents-from virtual creatures to physical robots-by jointly optimizing their morphologies and controllers rather than treating control in isolation. This integrated approach facilitates richer environmental interactions and robust task performance. In this survey, we provide a systematic overview of recent advances in ECD. We first formalize the concept of ECD and position it within related fields. We then introduce a hierarchical taxonomy: a lower layer that breaks down agent design into three fundamental components-controlling brain, body morphology, and task environment-and an upper layer that integrates these components into four major ECD frameworks: bi-level, single-level, generative, and open-ended. This taxonomy allows us to synthesize insights from more than one hundred recent studies. We further review notable benchmarks, datasets, and applications in both simulated and real-world scenarios. Finally, we identify significant challenges and offer insights into promising future research directions. A project associated with this survey has been created at https://github.com/Yuxing-Wang-THU/SurveyBrainBody.
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