DocumentCode :
339544
Title :
The Gaussian sampling strategy for probabilistic roadmap planners
Author :
Boor, Valdrie ; Overmars, Mark H. ; Van der Stappen, A. Frank
Author_Institution :
Dept. of Comput. Sci., Utrecht Univ., Netherlands
Volume :
2
fYear :
1999
fDate :
1999
Firstpage :
1018
Abstract :
Probabilistic roadmap planners (PRMs) form a relatively new technique for motion planning that has shown great potential. A critical aspect of PRM is the probabilistic strategy used to sample the free configuration space. In this paper we present a new, simple sampling strategy, which we call the Gaussian sampler, that gives a much better coverage of the difficult parts of the free configuration space. The approach uses only elementary operations which makes it suitable for many different planning problems. Experiments indicate that the technique is very efficient indeed
Keywords :
Gaussian processes; mobile robots; path planning; probability; Gaussian sampling; configuration space; mobile robots; motion planning; path planning; probabilistic roadmap planners; Books; Computer science; Genetic algorithms; Layout; Mobile robots; Motion planning; Neural networks; Orbital robotics; Path planning; Sampling methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference on
Conference_Location :
Detroit, MI
ISSN :
1050-4729
Print_ISBN :
0-7803-5180-0
Type :
conf
DOI :
10.1109/ROBOT.1999.772447
Filename :
772447
Link To Document :
بازگشت