Distributed Sampling-Based Roadmap of Trees for Large-Scale Motion Planning
Distributed Sampling-Based Roadmap of Trees for Large-Scale Motion Planning
复制标题
用于大规模运动规划的基于分布式采样的树路线图
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
L. Kavraki
中科院分区：
文献类型：
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作者：
E. Plaku;L. Kavraki
复杂的机器人系统所产生的高维问题测试当前的运动规划的限制，并需要开发有效的分布式运动规划，充分利用所有可用的资源。本文展示了如何有效地分配基于采样的路线图树（SRT）算法的计算使用分散的主客户端计划。分布式SRT算法使我们能够解决非常高维的问题，不能有效地解决与现有的规划。我们的实验表明，近线性的加速比与80个处理器，并表明，类似的加速比，可以得到几百个处理器。
High-dimensional problems arising from complex robotic systems test the limits of current motion planners and require the development of efficient distributed motion planners that take full advantage of all the available resources. This paper shows how to effectively distribute the computation of the Sampling-based Roadmap of Trees (SRT) algorithm using a decentralized master-client scheme. The distributed SRT algorithm allows us to solve very high-dimensional problems that cannot be efficiently addressed with existing planners. Our experiments show nearly linear speedups with eighty processors and indicate that similar speedups can be obtained with several hundred processors.