Knowledge Commons of Institute of Automation,CAS
Online Optimization of Normalized CPGs for a Multi-Joint Robotic Fish | |
Tong R(仝茹); Wu ZX(吴正兴); Wang J(王健); Tan M(谭民); Yu JZ(喻俊志) | |
2021-07 | |
会议名称 | 2021 40th Chinese Control Conference (CCC) |
会议日期 | 2021年7月 |
会议地点 | 中国,上海 |
摘要 | As a popular control rhythm of the multi-joint robotic fish, Center Pattern Generators (CPGs) plays an important role for motion performance. However, its optimal parameters are tough to seek through traditional methods. In order to address this problem, we propose an online optimization method for CPG parameters, including a novel normalized CPGs (N-CPGs) and a learning-based optimization algorithm. Via N-CPGs, the network parameters can be fully decoupled, which provides a great convenience for model parameter optimization. In particular, by applying the established dynamic model of the robotic fish, we use the deep Q network (DQN) to optimize the N-CPGs, aiming at improving the speed performance. Finally, extensive simulation results verify the effectiveness of proposed method, laying a solid foundation for real-time online control optimization of versatile motion modes in complex application scenarios. |
是否为代表性论文 | 否 |
七大方向——子方向分类 | 智能机器人 |
国重实验室规划方向分类 | 水下仿生机器人 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57604 |
专题 | 复杂系统认知与决策实验室_水下机器人 |
通讯作者 | Yu JZ(喻俊志) |
作者单位 | 1.中国科学院大学 2.中国科学院自动化研究所 3.北京大学 |
推荐引用方式 GB/T 7714 | Tong R,Wu ZX,Wang J,et al. Online Optimization of Normalized CPGs for a Multi-Joint Robotic Fish[C],2021. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Tong et al_2021_Onli(456KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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