Human-like ZMP Generator and Walking Stabilizer based on Divergent Component of Motion

被引：0
|
作者：
Wang, Haitao [1 ]
Tian, Zhongyuan [1 ]
Hu, Wenbin [1 ]
Zhao, Mingguo [1 ,2 ]
机构：
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] Tsinghua Univ, CBICR, Beijing Innovat Ctr Future Chip, Beijing 100084, Peoples R China
来源：
2018 IEEE-RAS 18TH INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS) | 2018年
关键词：
D O I：
暂无
中图分类号：
TP24 [机器人技术];
学科分类号：
080202 ; 1405 ;
摘要：
To realize natural and fast bipedal walking, we mimic the ZMP trajectory from human walking data based on the concept of Divergent Component of Motion (DCM). This paper presents an omnidirectional gait generator that is lightweight and universal. In addition, we integrate DCM tracking and foot placement adjustment into our control framework to ensure a stable walking motion and push recovery. The method proposed was validated in RoboCup2018 AdultSize soccer competition, where our robot WALKER+ walked on grass field and kept balance after the push from other robots.
引用
收藏
页码：82 / 87
页数：6
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