{"title":"A general robot environment understanding approach inspired by biological visual cortex","authors":"Xilong Liu, Zhiqiang Cao, J. Jiao, Kun Ai, M. Tan","doi":"10.1109/ROBIO.2013.6739755","DOIUrl":null,"url":null,"abstract":"A general vision approach for environment understanding of mobile robot is proposed, which is inspired by biological visual cortex. Gray level image from robot camera is firstly processed in the selective attention layer, and then in S and C layers for meaningful structure elements. With the help of the Sc layer designed for endpoints detection, the line segments map is generated to serve as the form of environment understanding results. Experiments on mobile robot are implemented by the task of avoiding obstacles with different sizes and shapes, pits, sharp cliffs, et al. The experimental results demonstrate the adaptability and versatility of the proposed approach.","PeriodicalId":434960,"journal":{"name":"2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO.2013.6739755","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A general vision approach for environment understanding of mobile robot is proposed, which is inspired by biological visual cortex. Gray level image from robot camera is firstly processed in the selective attention layer, and then in S and C layers for meaningful structure elements. With the help of the Sc layer designed for endpoints detection, the line segments map is generated to serve as the form of environment understanding results. Experiments on mobile robot are implemented by the task of avoiding obstacles with different sizes and shapes, pits, sharp cliffs, et al. The experimental results demonstrate the adaptability and versatility of the proposed approach.