{"title":"Design of a peristaltic crawling robot using 3-D link mechanisms","authors":"N. Saga, S. Tesen, Hiroki Dobashi, J. Nagase","doi":"10.1504/IJBBR.2013.058739","DOIUrl":null,"url":null,"abstract":"In disaster areas, rescue work conducted by humans is extremely difficult. Therefore, rescue work using rescue robots in place of humans is attracting attention. This study specifically examines peristaltic crawling, the movement mechanism of an earthworm, because it can enable movement through narrow spaces and because it can provide stable movement according to various difficult environments. We developed a robot using peristalsis characteristics and derived a robot motion pattern using Q-learning, a mode of reinforcement learning. Moreover, we designed each part of the robot based on required specifications and thereby developed a real robot. We present results of motion experiments assessing the robot’s level ground movement.","PeriodicalId":375470,"journal":{"name":"International Journal of Biomechatronics and Biomedical Robotics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Biomechatronics and Biomedical Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJBBR.2013.058739","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In disaster areas, rescue work conducted by humans is extremely difficult. Therefore, rescue work using rescue robots in place of humans is attracting attention. This study specifically examines peristaltic crawling, the movement mechanism of an earthworm, because it can enable movement through narrow spaces and because it can provide stable movement according to various difficult environments. We developed a robot using peristalsis characteristics and derived a robot motion pattern using Q-learning, a mode of reinforcement learning. Moreover, we designed each part of the robot based on required specifications and thereby developed a real robot. We present results of motion experiments assessing the robot’s level ground movement.