{"title":"多四足机器人步态同步的分布式模型预测编队控制","authors":"Shaohang Xu, Wentao Zhang, Lijun Zhu, C. Ho","doi":"10.1109/ICRA48891.2023.10161260","DOIUrl":null,"url":null,"abstract":"In this paper, we present a fully distributed framework for multiple quadruped robots in environments with obstacles. Our approach utilizes Model Predictive Control (MPC) and multi-robot consensus protocol to obtain the distributed control law. It ensures that all the robots are able to avoid obstacles, navigate to the desired positions, and meanwhile synchronize the gaits. In particular, via MPC and consensus, the robots compute the optimal trajectory and the contact profile of the legs. Then an MPC-based locomotion controller is implemented to achieve the gait, stabilize the locomotion and track the desired trajectory. We present experiments in simulation and with three real quadruped robots in an environment with a static obstacle.","PeriodicalId":360533,"journal":{"name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distributed Model Predictive Formation Control with Gait Synchronization for Multiple Quadruped Robots\",\"authors\":\"Shaohang Xu, Wentao Zhang, Lijun Zhu, C. Ho\",\"doi\":\"10.1109/ICRA48891.2023.10161260\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a fully distributed framework for multiple quadruped robots in environments with obstacles. Our approach utilizes Model Predictive Control (MPC) and multi-robot consensus protocol to obtain the distributed control law. It ensures that all the robots are able to avoid obstacles, navigate to the desired positions, and meanwhile synchronize the gaits. In particular, via MPC and consensus, the robots compute the optimal trajectory and the contact profile of the legs. Then an MPC-based locomotion controller is implemented to achieve the gait, stabilize the locomotion and track the desired trajectory. We present experiments in simulation and with three real quadruped robots in an environment with a static obstacle.\",\"PeriodicalId\":360533,\"journal\":{\"name\":\"2023 IEEE International Conference on Robotics and Automation (ICRA)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Robotics and Automation (ICRA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRA48891.2023.10161260\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Robotics and Automation (ICRA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRA48891.2023.10161260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed Model Predictive Formation Control with Gait Synchronization for Multiple Quadruped Robots
In this paper, we present a fully distributed framework for multiple quadruped robots in environments with obstacles. Our approach utilizes Model Predictive Control (MPC) and multi-robot consensus protocol to obtain the distributed control law. It ensures that all the robots are able to avoid obstacles, navigate to the desired positions, and meanwhile synchronize the gaits. In particular, via MPC and consensus, the robots compute the optimal trajectory and the contact profile of the legs. Then an MPC-based locomotion controller is implemented to achieve the gait, stabilize the locomotion and track the desired trajectory. We present experiments in simulation and with three real quadruped robots in an environment with a static obstacle.