摘要
针对在电池能源受限、响应时间受限、作业空间受限等复杂环境中的作业需求,本文提出了一种基于中枢模式发生器(Central Pattern Generator,CPG)的仿生分层控制框架,并将其应用于两栖机器人上,通过CPG产生机器人的不同运动模态,并进一步探讨利用学习方法(Learning-based)优化机器人的实际运动策略。最后,在仿生飞爬机器人原型机上进行实验测试,验证了所提出的仿生分层控制框架的可行性和有效性。
In order to operate in complex environments where energy,time and working space are limited,a bioinspired hierarchical control framework based on Central Pattern Generator(CPG)for terrestrial-aerial robots is proposed in this paper.Different locomotion modes of the robot are generated via CPG,and the actual motion strategies of the robot are further optimized by learning-based methods.Finally,the feasibility and effectiveness of the proposed bioinspired hierarchical control framework are verified by experimental tests applied on the bionic flying-climbing robot prototype.
作者
欧阳文娟
王超
陆磊丰
边慧杰
李伟鹏
OUYANG Wenjuan;WANG Chao;LU Leifeng;BIAN Huijie;LI Weipeng(China Nanhu Academy of Electronics and Information Technology,Jiaxing 314002,China)
出处
《智能物联技术》
2023年第2期11-15,44,共6页
Technology of Io T& AI
基金
中国电子科技南湖研究院研发项目。
关键词
两栖机器人
中枢模式发生器
仿生控制
terrestrial-aerial robots
central pattern generator
bioinspired control
