Title
Localization of unknown odor source based on Shannon's entropy using multiple mobile robots
Abstract
This paper deals with the problem of odor source localization by designing a collective decision-making mechanism based on Shannon's entropy and using two finite-time motion control algorithms for multiple mobile robots. Specifically, for the collective decision-making mechanism, a discrete grid map is first used to model the search environment. Then, the posteriori probability distribution for the position of the odor source on the discrete grid map is recursively updated by the detection events and non-detection events. Next, the Shannon's entropy for the probability distribution is employed to collectively make the decision on the movement direction of the robot group. For the motion control, the finite-time parallel motion control algorithm and the finite-time circular motion control algorithm are described. Moreover, two motion control algorithms are further extended in order to enable the robot group to avoid obstacles. Finally, the effective of the collective decision-making mechanism and two finite-time motion control algorithms is illustrated for the problem of odor source localization.
Year
DOI
Venue
2014
10.1109/IECON.2014.7048904
IECON
Keywords
DocType
ISSN
collision avoidance,decision making,electronic noses,entropy,mobile robots,motion control,multi-robot systems,statistical distributions,shannon entropy,collective decision-making mechanism,detection events,discrete grid map,finite-time circular motion control algorithm,finite-time motion control algorithms,finite-time parallel motion control algorithm,multiple mobile robots,obstacles avoidance,odor source localization,odor source position,posteriori probability distribution,robot group movement direction,search environment,shannon's entropy,probability distribution,robot kinematics
Conference
1553-572X
Citations 
PageRank 
References 
1
0.35
6
Authors
3
Name
Order
Citations
PageRank
Qiang Lu1273.84
Yang He2143.56
Jian Wang3265.72