{"title":"基于近端策略优化强化学习的履带式救援机器人阶梯攀爬方法","authors":"Mifu Totani, N. Sato, Y. Morita","doi":"10.1109/RoMoCo.2019.8787360","DOIUrl":null,"url":null,"abstract":"It is a huge burden on an operator when he/she tele-operates a rescue robot traveling on a rough terrain. Therefore, the purpose of this study is to reduce this burden by controlling the robot autonomously. As a first step, we propose a step climbing method for a crawler type rescue robot by using reinforcement learning with Proximal Policy Optimization (PPO). The input data are the image of a camera on the robot and a posture image of the robot. We verified the effectiveness of the proposed method using a dynamics simulator.","PeriodicalId":415070,"journal":{"name":"2019 12th International Workshop on Robot Motion and Control (RoMoCo)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Step climbing method for crawler type rescue robot using reinforcement learning with Proximal Policy Optimization\",\"authors\":\"Mifu Totani, N. Sato, Y. Morita\",\"doi\":\"10.1109/RoMoCo.2019.8787360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is a huge burden on an operator when he/she tele-operates a rescue robot traveling on a rough terrain. Therefore, the purpose of this study is to reduce this burden by controlling the robot autonomously. As a first step, we propose a step climbing method for a crawler type rescue robot by using reinforcement learning with Proximal Policy Optimization (PPO). The input data are the image of a camera on the robot and a posture image of the robot. We verified the effectiveness of the proposed method using a dynamics simulator.\",\"PeriodicalId\":415070,\"journal\":{\"name\":\"2019 12th International Workshop on Robot Motion and Control (RoMoCo)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 12th International Workshop on Robot Motion and Control (RoMoCo)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RoMoCo.2019.8787360\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 12th International Workshop on Robot Motion and Control (RoMoCo)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RoMoCo.2019.8787360","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Step climbing method for crawler type rescue robot using reinforcement learning with Proximal Policy Optimization
It is a huge burden on an operator when he/she tele-operates a rescue robot traveling on a rough terrain. Therefore, the purpose of this study is to reduce this burden by controlling the robot autonomously. As a first step, we propose a step climbing method for a crawler type rescue robot by using reinforcement learning with Proximal Policy Optimization (PPO). The input data are the image of a camera on the robot and a posture image of the robot. We verified the effectiveness of the proposed method using a dynamics simulator.
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