A Configuration Deactivation Algorithm for Boosting Probabilistic Roadmap Planning of Robots  

作　　者：Mika T. Rantanen Martti Juhola 

机构地区：[1]Computer Sciences, School of Information Sciences, University of Tampere

出　　处：《International Journal of Automation and computing》2012年第2期155-164,共10页国际自动化与计算杂志（英文版）

摘　　要：We present a method to improve the execution time used to build the roadmap in probabilistic roadmap planners. Our method intelligently deactivates some of the configurations during the learning phase and allows the planner to concentrate on those configurations that axe most likely going to be useful when building the roadmap. The method can be used with many of the existing sampling algorithms. We ran tests with four simulated robot problems typical in robotics literature. The sampling methods applied were purely random, using Halton numbers, Gaussian distribution, and bridge test technique. In our tests, the deactivation method clearly improved the execution times. Compared with pure random selections, the deactivation method also significantly decreased the size of the roadmap, which is a useful property to simplify roadmap planning tasks.We present a method to improve the execution time used to build the roadmap in probabilistic roadmap planners. Our method intelligently deactivates some of the configurations during the learning phase and allows the planner to concentrate on those configurations that axe most likely going to be useful when building the roadmap. The method can be used with many of the existing sampling algorithms. We ran tests with four simulated robot problems typical in robotics literature. The sampling methods applied were purely random, using Halton numbers, Gaussian distribution, and bridge test technique. In our tests, the deactivation method clearly improved the execution times. Compared with pure random selections, the deactivation method also significantly decreased the size of the roadmap, which is a useful property to simplify roadmap planning tasks.

关 键 词：Probabilistic roadmaps motion planning collision avoidance sampling algorithms robotics. 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]