{"title":"Spydobot-AI Based autonomous spider like robot for spying","authors":"Jamal Pasha, S. Karpagavalli","doi":"10.1109/CONECCT55679.2022.9865761","DOIUrl":null,"url":null,"abstract":"Autonomous companion robots have shown to be particularly beneficial for gathering information in areas where people are restricted. Controlling them is often a challenge ng feat due to the environment's ambiguity and the nonlinear dynamics of the grounds. Despite the fact that a variety of controller designs are feasible, and some are documented in the literature, it is unknown which designs are best suited for a certain context. In this paper, we attempted to design a robot that can be adapted for usage in any environment by making only skeleton alterations, we designed the controller with integrating Neural network nodes with Q-learning algorithm to regulate movement of the robot using LIDAR samples. With military applications in consideration, we implemented encryptors to send and receive data, and we distributed all dumps to the controller to ensure that we only needed to be connected when delivering data to the owner. As all this requires high processing speed and storage, we recommend using ESP32-S2 for its high clock speed.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONECCT55679.2022.9865761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Autonomous companion robots have shown to be particularly beneficial for gathering information in areas where people are restricted. Controlling them is often a challenge ng feat due to the environment's ambiguity and the nonlinear dynamics of the grounds. Despite the fact that a variety of controller designs are feasible, and some are documented in the literature, it is unknown which designs are best suited for a certain context. In this paper, we attempted to design a robot that can be adapted for usage in any environment by making only skeleton alterations, we designed the controller with integrating Neural network nodes with Q-learning algorithm to regulate movement of the robot using LIDAR samples. With military applications in consideration, we implemented encryptors to send and receive data, and we distributed all dumps to the controller to ensure that we only needed to be connected when delivering data to the owner. As all this requires high processing speed and storage, we recommend using ESP32-S2 for its high clock speed.