{"title":"A Miniature Pole-Climbing Piezoelectric Robot With Fast and Load-Towable Movement Inspired by Squirrel’s Galloping Gait","authors":"Xiang Li;Zhaochun Ding;Jiang Wu;Wentao Wei;Lipeng Wang;Yanhu Zhang;Dong Li;Xuewen Rong;Rui Song;Yibin Li","doi":"10.1109/TIE.2024.3481878","DOIUrl":null,"url":null,"abstract":"This article presents a miniature pole-climbing piezoelectric robot (MPCPR) with fast and load-towable movement. Basically, it incorporates a pair of alumina transducers, where the third bending (B3) and second bending (B2) vibrations are excited independently in the time domain to enable the MPCPR to climb up and down the external tubes; this interestingly imitates the squirrel’s galloping gait when it climbs trees. First, the transducer was structurally optimized by constructing a Krimhertz-transmission-theory-based model to enhance the driving-force-to-weight ratio. Then, a prototype 60 × 60 × 60 mm<sup>3</sup> in size and 40.2 g in weight was fabricated, and its climbing/towing/positioning performance was assessed. At 37.22 kHz working frequency and 30 V voltage, the MPCPR produced the maximal climbing-up speed of 183.2 mm/s and the maximal towing weight of 225 g (equal to 5.6 times its self-weight). It could climb up the tubes in circular/rectangular shapes, whose diameters/lengths were in the range of 12–28 mm. In stepping operation, it yielded the minimal step displacement of 0.32 μm. This article validates the MPCPR’s high climbing/towing capability and offers an approach to design powerful piezoelectric robots with the function of vertically climbing up external tubes.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 5","pages":"5221-5233"},"PeriodicalIF":7.2000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10739864/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents a miniature pole-climbing piezoelectric robot (MPCPR) with fast and load-towable movement. Basically, it incorporates a pair of alumina transducers, where the third bending (B3) and second bending (B2) vibrations are excited independently in the time domain to enable the MPCPR to climb up and down the external tubes; this interestingly imitates the squirrel’s galloping gait when it climbs trees. First, the transducer was structurally optimized by constructing a Krimhertz-transmission-theory-based model to enhance the driving-force-to-weight ratio. Then, a prototype 60 × 60 × 60 mm3 in size and 40.2 g in weight was fabricated, and its climbing/towing/positioning performance was assessed. At 37.22 kHz working frequency and 30 V voltage, the MPCPR produced the maximal climbing-up speed of 183.2 mm/s and the maximal towing weight of 225 g (equal to 5.6 times its self-weight). It could climb up the tubes in circular/rectangular shapes, whose diameters/lengths were in the range of 12–28 mm. In stepping operation, it yielded the minimal step displacement of 0.32 μm. This article validates the MPCPR’s high climbing/towing capability and offers an approach to design powerful piezoelectric robots with the function of vertically climbing up external tubes.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.