DocumentCode :
404702
Title :
Entropy-based environment exploration and stochastic optimal control
Author :
Baglietto, M. ; Paolucci, M. ; Scardovi, L. ; Zoppoli, R.
Author_Institution :
Dept. of Commun., Comput. & Syst. Sci., Genoa Univ., Italy
Volume :
3
fYear :
2003
fDate :
9-12 Dec. 2003
Firstpage :
2938
Abstract :
This paper deals with the problem of mapping an unknown environment by a team of autonomous decision makers. A discrete grid map of the environment is considered in which each cell is labeled as free or not free, depending on the presence of an obstacle. The decision makers can communicate with one another. A preliminary study of the problem in the framework of stochastic optimal control is presented. The tradeoff between the exploration cost and the information gain (exploiting the concept of entropy) is addressed. Numerical results show the effectiveness of the approach.
Keywords :
artificial intelligence; entropy; optimal control; path planning; robots; stochastic systems; autonomous decision makers; discrete grid map; entropy-based environment exploration; stochastic optimal control; Adaptive control; Costs; Data analysis; Delta modulation; Entropy; Mobile communication; Optimal control; Robots; Stochastic processes; Stochastic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
ISSN :
0191-2216
Print_ISBN :
0-7803-7924-1
Type :
conf
DOI :
10.1109/CDC.2003.1273072
Filename :
1273072
Link To Document :
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