Paper Info
Title
Computation Sharing in Distributed Robotic Systems: A Case Study on SLAM
Abstract
Aiming at increasing team efficiency, mobile robots may act as a node of a Robotic Cluster to assist their teammates in computationally demanding tasks. Having this in mind, we propose two distributed architectures for the Simultaneous Localization And Mapping (SLAM) problem, our main case study. The analysis focuses especially on the efficiency gain that can be obtained. It is shown that the proposed architectures enable us to raise the workload up to values that would not be possible in a single robot solution, thus gaining in localization precision and map accuracy. Furthermore, we assess the impact of network bandwidth. All the results are extracted from frequently used SLAM datasets available in the robotics community and a real world testbed is described to show the potential of using the proposed philosophy.
Year
DOI
Venue
2015
10.1109/TASE.2014.2357216
Automation Science and Engineering, IEEE Transactions  
Keywords
Field
DocType
Simultaneous localization and mapping,Computer architecture,Robot kinematics,Multi-robot systems,Context
Robot control,Computer science,Testbed,Robot kinematics,Bandwidth (signal processing),Artificial intelligence,Robot,Simultaneous localization and mapping,Robotics,Mobile robot,Distributed computing
Journal
Volume
Issue
ISSN
12
2
1545-5955
Citations 
PageRank 
References 
13
0.67
16
Authors
4
Name
Order
Citations
PageRank
Bruno D. Gouveia1161.21
David Portugal217518.74
Daniel C. Silva3130.67
Lino Marques440747.76