.png){kind=icon}
返回
Efficient Configuration Space Construction and Optimization for Motion Planning
.png){kind=icon}
OA
AI
DOI：10.15302/J-ENG-2015009.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The configuration space is a fundamental concept that is widely used in algorithmic robotics. Many applications in robotics, computer-aided design, and related areas can be reduced to computational problems in terms of configuration spaces. In this paper, we survey some of our recent work on solving two important challenges related to configuration spaces: 1 how to efficiently compute an approximate representation of high-dimensional configuration spaces; and 72, how to efficiently perform geometric proximity and motion planning queries in high-dimensional configuration spaces. We present new configuration space construction algorithms based on machine learning and geometric approximation techniques. These algorithms perform collision queries on many configuration samples. The collision query results are used to compute an approximate representation for the configuration space, which quickly converges to the exact configuration space. We also present parallel GPU-based algorithms to accelerate the performance of optimization and search computations in configuration spaces. In particular, we design efficient GPU-based parallel k-nearest neighbor and parallel collision detection algorithms and use these algorithms to accelerate motion planning.
Keyword:
configuration space
motion planning
GPU parallel algorithm
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:
11.6
论文数:
2.7K
被引数:
1.5W
机构
引用论文
Observation of Long Supershear Rupture During the Magnitude 8.1 Kunlunshan Earthquake.png)
Science
ScienceIF0
PREAI
分享收藏Ultra-sensitive phosphorescence sensor for the detection of trace As(v) based on the signal amplification effect of As(v) catalyzing H2O2 oxidize CdTe-Cys-quantum dotsRSC Advances
RSC AdvancesIF0
PREAI
分享收藏分享收藏
查看更多内容