.png){kind=icon}
返回
Exploiting Sparsity in Operational-space Dynamics
.png){kind=icon}
OA
AI
DOI：10.1177/0278364909357644.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper presents a new method for calculating operational-space inertia matrices, and other related quantities, for branched kinematic trees. It is based on the exploitation of branch-induced sparsity in the joint-space inertia matrix and the task Jacobian. Detailed cost figures are given for the new method, and its efficacy is demonstrated by means of a realistic example based on the ASIMO Next-Generation humanoid robot. In this example, the new method is shown to be 6.7 times faster than the basic matrix method, and 1.6 times faster than the efficient low-order algorithm of Rodriguez et al. Furthermore, cost savings of more than 50,000 arithmetic operations are obtained in the calculation of the inertia-weighted pseudoinverse of the task Jacobian and its null-space projection matrix. Additional examples are considered briefly, in order to further compare the new method with the algorithm of Rodriguez et al.
Keyword:
brain-induced sparsity
operational-space intertia
humanoids
robot dynamics
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5
论文数:
2.4K
被引数:
1.5W
机构
暂无机构信息
引用论文
Molecular characterization of cDNAs encoding squirrel monkey ( Saïmiri sciureus ) CD8 α and β chains
PREAI
分享收藏Analytical model of the LPL with wake up after transmissions MAC protocol for WSNs无线传感器网络中具有传输后唤醒的LPL MAC协议的分析模型
PREAI
分享收藏Unraveling snake venom complexity with ‘omics’ approaches: Challenges and perspectives.png)
Toxicon
ToxiconIF0
PREAI
分享收藏Leveraging Automation toward Development of a High-Throughput Gene Expression Profiling PlatformOAAI
OAAI分享收藏
查看更多内容