Paper Info
Title
A framework for topological based map building: A solution to autonomous robot navigation in smart cities
Abstract
Advancement in the Information and Communications Technology (ICT) has transformed urban environments into modern smart cities by connecting physical devices or sensors to communicate via the Internet of things (IoT) networks. These sensors collect a massive amount of data, which is eventually used in the efficient management of shared assets and resources. In this article, we provide a framework for topological based map building for autonomous robot navigation in smart cities supporting IoT-based technologies. The classical methods of topological based map building do not incorporate the real essence of topology but instead, an illustration is provided where the topology is considered to be a cluster of features. We analyzed the problem of map building from a pure robotic perspective by considering the shape of free-space into a robot navigation path. In the proposed framework, shape-based invariant features are extracted from the free-space, which are used in the construction of topological nodes for robot autonomous navigation. In the context of topological navigation, topology is considered as a structural representation of connecting nodes representing free-space shapes and edges that define their connectivity. To evaluate the performance of the proposed approach, real-time experiments are performed, which show improvements in autonomous navigation in terms of efficiency and maneuverability.
Year
DOI
Venue
2020
10.1016/j.future.2019.10.036
Future Generation Computer Systems
Keywords
DocType
Volume
Internet of things,Smart cities,Topological maps,Autonomous robot navigation,Topo-metric mapping,Fourier descriptors,Image moments,Shape features
Journal
111
ISSN
Citations 
PageRank 
0167-739X
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Naveed Islam1376.58
Khalid Haseeb2608.87
ahmad almogren327435.54
Ikram Ud Din47916.80
Mohsen Guizani56456557.44
Ayman Altameem6929.17