Paper Info
Title
Distributed collaborative localization for a heterogeneous multi-robot system
Abstract
This paper studies the problem of collaborative localization for a heterogeneous multi-robotic system (MRS), particularly an MRS with one or more robots with accurate self-localization capabilities (leader) and several robots with little or no such capabilities (child). Finite-range sensing is one of the major limitation in the collaboration of an MRS when the child robots rely on inter-robot relative measurements (IRRM) between themselves and the leader robot for localization. This study proposes a collaborative localization (CL) scheme, which has the ability to localize child robots even when they operate beyond the field of view (FOV) of the leader robots. A distributed sensor fusion architecture is introduced in order to reduce the communication bandwidth, processing power, and memory usage requirements for the leader robot. Thus, the resulting implementation is scalable in terms of the number of robots in the team. The performance of the proposed localization scheme was evaluated in Monte Carlo simulations and a series of experiments using a team of six mobile robots. Both the experiment and the simulation results demonstrated that the proposed CL scheme is capable of establishing a localization for child robots with 1~10 cm positional accuracy and 0.01~0.1 rad orientational accuracy, even when they operate beyond the FOV of the leader robot.
Year
DOI
Venue
2014
10.1109/CCECE.2014.6900998
Electrical and Computer Engineering
Keywords
Field
DocType
Monte Carlo methods,mobile robots,multi-robot systems,path planning,sensor fusion,CL scheme,MRS,Monte Carlo simulations,child robots,communication bandwidth reduction,distributed collaborative localization scheme,distributed sensor fusion architecture,field-of-view,finite-range sensing,heterogeneous multirobot system,interrobot relative measurements,memory usage requirement reduction,mobile robots,processing power reduction,self-localization capabilities
Field of view,Computer science,Real-time computing,Control engineering,Communication bandwidth,Artificial intelligence,Robotic systems,Computer vision,Monte Carlo method,Sensor fusion,Robot,Mobile robot,Scalability
Conference
ISSN
Citations 
PageRank 
0840-7789
2
0.36
References 
Authors
10
3
Name
Order
Citations
PageRank
Thumeera R. Wanasinghe1343.37
Mann, G.K.I.213913.77
Gosine, R.G.38510.46