人工智能
机器人学
计算机科学
稳健性(进化)
人机交互
软件部署
机器人
系统工程
组分(热力学)
多模态
环境智能
钥匙(锁)
范式转换
重新调整用途
工程类
领域
利用
运动规划
仿生学
重大挑战
软机器人
系统集成
作者
Ziyu Ren,Youning Duo,Haoyuan Xu,Yihui Zhang,Xingjian Liu,Jamie Paik,Auke Jan Ijspeert,Li Wen
出处
期刊:Science robotics
[American Association for the Advancement of Science]
日期:2026-07-22
卷期号:11 (116)
标识
DOI:10.1126/scirobotics.aea7639
摘要
To survive in dynamic and unstructured environments, animals have developed extraordinary multimodal locomotion capabilities. This biological insight drives the innovation of bioinspired multimodal robots, which are defined as robotic systems integrating and transitioning between two or more distinct modes of bioinspired locomotion. This Review explores the historical progression, key design considerations, and current challenges faced in the realm of multimodal robotics. We highlight recent advancements in robotic body design, including the integration of soft materials, innovative structure repurposing strategies, and the deployment of multirobot systems. These advancements facilitate seamless mode transitions through both active and passive structural reconfigurations. In the realm of path planning and motion control, the paradigm is progressively shifting from traditional graph-based approaches and discrete controllers to learning-based frameworks. To address the current void of standardized benchmarks in this field, we propose five performance metrics—number of modes, marginal cost of modality, component repurpose percentage, transition cost, and performance improvement—that provide a quantitative framework for evaluating multimodal robots in terms of design effectiveness and operational performance. Last, we delineate a strategic roadmap for the future that advocates for the integration of physical and computational intelligence in multimodal robotics, arguing that this convergence is crucial for enabling real-time behavioral adaptations to complex environmental stimuli and thereby enhancing the robustness and functionality of multimodal robotic systems.
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