NDLI: Metric embedding of view-graphs : A vision and odometry-based approach to cognitive mapping

Content Provider	Springer Nature Link
Author	Hübner, Wolfgang Mallot, Hanspeter A.
Copyright Year	2007
Abstract	Most recent robotic systems, capable of exploring unknown environments, use topological structures (graphs) as a spatial representation. Localization can be done by deriving an estimate of the global pose from landmark information. In this case navigation is tightly coupled to metric knowledge, and hence the derived control method is mainly pose-based. Alternative to continuous metric localization, it is also possible to base localization methods on weaker constraints, e.g. the similarity between images capturing the appearance of places or landmarks. In this case navigation can be controlled by a homing algorithm. Similarity based localization can be scaled to continuous metric localization by adding additional constraints, such as alignment of depth estimates. We present a method to scale a similarity based navigation system (the view-graph-model) to continuous metric localization. Instead of changing the landmark model, we embed the graph into the three dimensional pose space. Therefore, recalibration of the path integrator is only possible at discrete locations in the environment. The navigation behavior of the robot is controlled by a homing algorithm which combines three local navigation capabilities, obstacle avoidance, path integration, and scene based homing. This homing scheme allows automated adaptation to the environment. It is further used to compensate for path integration errors, and therefore allows to derive globally consistent pose estimates based on “weak” metric knowledge, i.e. knowledge solely derived from odometry. The system performance is tested with a robotic setup and with a simulated agent which explores a large, open, and cluttered environment.
Starting Page	183
Ending Page	196
Page Count	14
File Format	PDF
ISSN	09295593
Journal	Autonomous Robots
Volume Number	23
Issue Number	3
e-ISSN	15737527
Language	English
Publisher	Springer US
Publisher Date	2007-06-22
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Autonomous map building Simultaneous localization and mapping Cognitive mapping Simulation and Modeling Mechanical Engineering Computer Imaging, Vision, Pattern Recognition and Graphics Electronic and Computer Engineering Automation and Robotics Artificial Intelligence (incl. Robotics)
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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