DocumentCode :
2621512
Title :
Adaptive Sampling for Multi-Robot Wide-Area Exploration
Author :
Low, Kian Hsiang ; Gordon, Geoffrey J. ; Dolan, John M. ; Khosla, Pradeep
Author_Institution :
Carnegie Mellon Univ., Pittsburgh, PA
fYear :
2007
fDate :
10-14 April 2007
Firstpage :
755
Lastpage :
760
Abstract :
The exploration problem is a central issue in mobile robotics. A complete coverage is not practical if the environment is large with a few small hotspots, and the sampling cost is high. So, it is desirable to build robot teams that can coordinate to maximize sampling at these hotspots while minimizing resource costs, and consequently learn more accurately about properties of such environmental phenomena. An important issue in designing such teams is the exploration strategy. The contribution of this paper is in the evaluation of an adaptive exploration strategy called adaptive cluster sampling (ACS), which is demonstrated to reduce the resource costs (i.e., mission time and energy consumption) of a robot team, and yield more information about the environment by directing robot exploration towards hotspots. Due to the adaptive nature of the strategy, it is not obvious how the sampled data can be used to provide unbiased, low-variance estimates of the properties. This paper therefore discusses how estimators that are Rao-Blackwellized can be used to achieve low error. This paper also presents the first analysis of the characteristics of the environmental phenomena that favor the ACS strategy and estimators. Quantitative experimental results in a mineral prospecting task simulation show that our approach is more efficient in exploration by yielding more minerals and information with fewer resources and providing more precise mineral density estimates than previous methods.
Keywords :
adaptive signal processing; mobile robots; multi-robot systems; pattern clustering; signal sampling; Rao-Blackwellized estimators; adaptive cluster sampling; adaptive sampling; mobile robotics; multirobot wide-area exploration; robot team coordination; Condition monitoring; Costs; Extraterrestrial measurements; Intelligent robots; Mars; Minerals; Mobile robots; Robot kinematics; Robotics and automation; Sampling methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2007 IEEE International Conference on
Conference_Location :
Roma
ISSN :
1050-4729
Print_ISBN :
1-4244-0601-3
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ROBOT.2007.363077
Filename :
4209181
Link To Document :
بازگشت