Paper Info
Title
A Robust Exploration and Navigation Approach for Indoor Mobile Robots Merging Local and Global Strategies
Abstract
A mobile robot must explore its workspace in order to learn a map of its environment. Given the perceptual limitations and accuracy of its sensors, the robot has to stay close to obstacles in order to track its position and never get lost. This paper describes a new method for exploring and navigating autonomously in indoor environments. It merges a local strategy, similar to a wall following strategy to keep the robot close to obstacles, within a global search frame, based on a dynamic programming algorithm. This hybrid approach takes advantages of local strategies that consider perceptual limitations of sensors without losing the completeness of a global search. These methods for exploring and navigating are tested using a mobile robot simulator with very good results.
Year
DOI
Venue
2000
10.1007/3-540-44399-1_40
IBERAMIA-SBIA
Keywords
Field
DocType
perceptual limitation,global search frame,global strategies,navigation approach,indoor mobile robots merging,local strategy,mobile robot,navigating autonomously,robot close,robust exploration,global search,mobile robot simulator,dynamic programming algorithm,good result
Workspace,Computer science,Human–computer interaction,Voronoi diagram,Artificial intelligence,Distributed computing,Dynamic programming,Computer vision,Sensor fusion,Mobile robot navigation,Robot,Global strategy,Mobile robot
Conference
Volume
ISSN
ISBN
1952.0
0302-9743
3-540-41276-X
Citations 
PageRank 
References 
3
0.43
5
Authors
3
Name
Order
Citations
PageRank
Leonardo Romero1257.05
Eduardo F. Morales255957.67
Luis Enrique Sucar332.12