A plant-inspired kinematic model for growing robots

Emanuela Del Dottore, A. Mondini, A. Sadeghi, B. Mazzolai
{"title":"A plant-inspired kinematic model for growing robots","authors":"Emanuela Del Dottore, A. Mondini, A. Sadeghi, B. Mazzolai","doi":"10.1109/ROBOSOFT.2018.8404891","DOIUrl":null,"url":null,"abstract":"This paper presents a kinematic model inspired by plant growth strategies and used to describe the movement of a robotic root, able to self-build its body structure using a 3D printer-like mechanism embedded in its tip. The proposed model is implemented in simulation and validated through a comparative analysis of the position, in space, of the robotic and simulated tip, obtaining a maximal positional error of ∼7% with the smallest curvature radius within a curvature arc of ∼10 cm. The model is able to describe the motion of any robot that navigates its environment and moves by growing from the tip in a 3D space, and it has been validated on a plant-inspired robot. The new emerging generation of growing robots offers an alternative locomotion perspective in robotics, which is grounded on the ability of this kind of bioinspired robots to morphologically and dynamically adapt their body to surrounding environments, offering new scenarios of use in search and rescue tasks, and hazardous conditions.","PeriodicalId":306255,"journal":{"name":"2018 IEEE International Conference on Soft Robotics (RoboSoft)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Soft Robotics (RoboSoft)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOSOFT.2018.8404891","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

This paper presents a kinematic model inspired by plant growth strategies and used to describe the movement of a robotic root, able to self-build its body structure using a 3D printer-like mechanism embedded in its tip. The proposed model is implemented in simulation and validated through a comparative analysis of the position, in space, of the robotic and simulated tip, obtaining a maximal positional error of ∼7% with the smallest curvature radius within a curvature arc of ∼10 cm. The model is able to describe the motion of any robot that navigates its environment and moves by growing from the tip in a 3D space, and it has been validated on a plant-inspired robot. The new emerging generation of growing robots offers an alternative locomotion perspective in robotics, which is grounded on the ability of this kind of bioinspired robots to morphologically and dynamically adapt their body to surrounding environments, offering new scenarios of use in search and rescue tasks, and hazardous conditions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
植物启发的生长机器人运动学模型
本文提出了一个受植物生长策略启发的运动学模型,用于描述机器人根的运动,能够使用嵌入在其尖端的类似3D打印机的机构自构建其身体结构。该模型已在仿真中实现,并通过对机器人和模拟尖端在空间中的位置进行比较分析来验证,在曲率弧内的最小曲率半径为~ 10 cm,最大位置误差为~ 7%。该模型能够描述任何机器人在其环境中导航的运动,并通过在3D空间中从尖端生长来移动,并且已经在一个受植物启发的机器人上进行了验证。新一代的成长机器人为机器人技术提供了另一种运动视角,这是基于这种仿生机器人能够在形态上和动态地适应周围环境的能力,为搜索和救援任务以及危险条件提供了新的使用场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Low profile stretch sensor for soft wearable robotics MultiTip: A multimodal mechano-thermal soft fingertip Trajectory tracking of a one-DOF manipulator using multiple fishing line actuators by iterative learning control Effect of base rotation on the controllability of a redundant soft robotic arm Strain sensor-embedded soft pneumatic actuators for extension and bending feedback
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1