SelSta - A Biologically Inspired Approach for Self-Stabilizing Humanoid Robot Walking

被引：0
|
作者：
Jakimovski, Bojan [1 ]
Kotke, Michael [1 ]
Hoerenz, Martin [1 ]
Maehle, Erik [1 ]
机构：
[1] Med Univ Lubeck, Inst Comp Engn, Lubeck, Germany
来源：
DISTRIBUTED, PARALLEL AND BIOLOGICALLY INSPIRED SYSTEMS | 2010年 / 329卷
关键词：
Self-stabilizing humanoid robot; S2-HuRo; biologically inspired approach; symbiosis; SelSta approach; humanoid robot walking optimization; SIMULATION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we elaborate a study on self-stabilizing humanoid robot that achieves run-time self-stabilization and energy optimized walking gait pattern parameters on different kinds of flat surfaces. The algorithmic approach named SelSta uses biologically inspired notions that introduce robustness into the self-stabilizing functionality of the humanoid robot. The approach has been practically tested on our S2-HuRo humanoid robot and the results from the tests demonstrate that it can be successfully used on humanoid robots to achieve autonomic optimized stabilization of their walking on different kinds of flat surfaces.
引用
收藏
页码：302 / 313
页数：12
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