{"title":"Sloth and slow loris inspired behavioral controller for a robotic agent","authors":"Lakshmi Velayudhan, R. Arkin","doi":"10.1109/ROBIO.2017.8324693","DOIUrl":null,"url":null,"abstract":"We explore the ethologically guided design of a robotic controller, inspired by sloth and slow loris behavior. These animals manage their energy expenditure efficiently under resource constrained environments through a combination of thermoregulatory and behavioral strategies. This has potential implications for the design of energy efficient mobile robots (or Slowbots) for long-term applications such as Precision Agriculture and Surveillance. In this paper, we compare two different behavioral coordination strategies, namely, Action Selection and Behavioral Fusion and evaluate their performances to determine the relative merits of each coordination strategy on the design of the Slowbot and its energy consumption.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO.2017.8324693","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
We explore the ethologically guided design of a robotic controller, inspired by sloth and slow loris behavior. These animals manage their energy expenditure efficiently under resource constrained environments through a combination of thermoregulatory and behavioral strategies. This has potential implications for the design of energy efficient mobile robots (or Slowbots) for long-term applications such as Precision Agriculture and Surveillance. In this paper, we compare two different behavioral coordination strategies, namely, Action Selection and Behavioral Fusion and evaluate their performances to determine the relative merits of each coordination strategy on the design of the Slowbot and its energy consumption.