A practical robot coverage algorithm for unknown environments

Authors:
Heung Seok Jeon;Myeong-Cheol Ko;Ryumduck Oh;Hyun Kyu Kang
Affiliations:
Department of Computer Science, Konkuk University, Chungju City, Korea;Department of Computer Science, Konkuk University, Chungju City, Korea;Department of Computer Science, Chungju National University, Chungju City, Korea;Department of Computer Science, Konkuk University, Chungju City, Korea
Venue:
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Year:
2010

Citing 8
Cited 0

A threshold of ln n for approximating set cover

Journal of the ACM (JACM)
The grid: blueprint for a new computing infrastructure

The grid: blueprint for a new computing infrastructure
FastSLAM: a factored solution to the simultaneous localization and mapping problem

Eighteenth national conference on Artificial intelligence
Grid Information Services for Distributed Resource Sharing

HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
FastSLAM 2.0: an improved particle filtering algorithm for simultaneous localization and mapping that provably converges

IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Coverage, exploration, and deployment by a mobile robot and communication network

IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
ZIB structure prediction pipeline: composing a complex biological workflow through web services

Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
A Practical Path Planner for the Robotic Vacuum Cleaner in Rectilinear Environments

IEEE Transactions on Consumer Electronics

Quantified Score

Hi-index	0.00

Visualization

Abstract

While there has been substantial research on coverage and SLAM algorithms, to our knowledge no previous research has considered using each of these algorithms with a service robot. As a result, the performance of these robots is less than adequate for most consumers, especially when the robots only rely on SLAM algorithms for their coverage services in an unknown environment. To address this problem, we propose a new coverage algorithm, AmaxCoverage, an area-maximizing coverage algorithm that efficiently integrates the SLAM solution. Our experimental results show that the AmaxCoverage algorithm outperforms previous representative coverage algorithms in unknown environments and therefore will increase consumers' confidence toward service robots.