Suppr超能文献

智能多模态移动和混合仿生附着的攀岩机器人。

Intelligent Rock-Climbing Robot Capable of Multimodal Locomotion and Hybrid Bioinspired Attachment.

机构信息

School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China.

School of Electro-mechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China.

出版信息

Adv Sci (Weinh). 2024 Oct;11(39):e2309058. doi: 10.1002/advs.202309058. Epub 2024 Jul 15.

Abstract

Rock-climbing robots have significant potential in fieldwork and planetary exploration. However, they currently face limitations such as a lack of stability and adaptability on extreme terrains, slow locomotion, and single functionality. This study introduces a novel multimodal and adaptive rock-climbing robot (MARCBot), which addresses these limitations through spiny grippers that draw inspiration from morpho-functionalities observed in beetles, arboreal birds, and hoofed animals. This hybrid bioinspired design enables high attachment strength, passive adaptability to different terrains, and quick attachment on rock surfaces. The multimodal functionality of the gripper allows for attachment during climbing and support during walking. A novel control strategy using dynamics and quadratic programming (QP) optimizes attachment wrench distribution, reducing cost-of-transport by 20.03% and 6.05% compared to closed-loop inverse kinematic (CLIK) and virtual model control (VMC) methods, respectively. MARCBot achieved climbing speeds of 0.15 m min on a vertical discrete rock surface under gravity and trotting speeds of up to 0.21 m s on various complex terrains. It is the first robot capable of climbing on rock surfaces and trotting in complex terrains without the need for switching end-effectors. This study highlights significant advancements in climbing and multimodal locomotion for robots in extreme environments.

摘要

攀岩机器人在野外工作和行星探索中具有重要的潜力。然而,它们目前在极端地形上存在稳定性和适应性差、运动速度慢以及功能单一等局限性。本研究介绍了一种新型的多模态自适应攀岩机器人(MARCBot),它通过借鉴甲虫、树栖鸟类和蹄类动物的形态功能而设计的刺状夹具来解决这些局限性。这种混合仿生设计能够实现高附着强度、对不同地形的被动适应性以及在岩石表面的快速附着。夹具的多模态功能允许在攀爬时附着,并在行走时提供支撑。使用动力学和二次规划(QP)的新型控制策略优化了附着扳手的分布,与闭环运动学逆解(CLIK)和虚拟模型控制(VMC)方法相比,分别降低了 20.03%和 6.05%的运输成本。MARCBot 在重力作用下能够以 0.15 m min 的速度在垂直离散的岩石表面上攀爬,并能够在各种复杂地形上以高达 0.21 m s 的速度小跑。它是第一台能够在没有切换末端执行器的情况下在岩石表面攀爬和在复杂地形上小跑的机器人。本研究突出了在极端环境中机器人的攀爬和多模态运动方面的重大进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0c1/11497113/79971a63face/ADVS-11-2309058-g013.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验