Localized qualitative navigation for indoor environments

Sgouros, NM; Papakonstantinou, G; Tsanakas, P

dc.contributor.author	Sgouros, NM	en
dc.contributor.author	Papakonstantinou, G	en
dc.contributor.author	Tsanakas, P	en
dc.date.accessioned	2014-03-01T02:41:14Z
dc.date.available	2014-03-01T02:41:14Z
dc.date.issued	1996	en
dc.identifier.issn	10504729	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30429
dc.subject	Indoor Environment	en
dc.subject	Linear Time	en
dc.subject	Numerical Simulation	en
dc.subject	Obstacle Detection	en
dc.subject	Path Planning	en
dc.subject	Position Estimation	en
dc.subject	Short Term Memory	en
dc.subject.other	Adaptive control systems	en
dc.subject.other	Collision avoidance	en
dc.subject.other	Computer simulation	en
dc.subject.other	Motion planning	en
dc.subject.other	Navigation	en
dc.subject.other	Online systems	en
dc.subject.other	Parameter estimation	en
dc.subject.other	Position control	en
dc.subject.other	Sensors	en
dc.subject.other	Topology	en
dc.subject.other	Indoor navigation	en
dc.subject.other	Localization	en
dc.subject.other	Obstacle detection	en
dc.subject.other	Obstacle orientation	en
dc.subject.other	Offline planner	en
dc.subject.other	Online controller	en
dc.subject.other	Position estimation	en
dc.subject.other	Mobile robots	en
dc.title	Localized qualitative navigation for indoor environments	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ROBOT.1996.503890	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ROBOT.1996.503890	en
heal.publicationDate	1996	en
heal.abstract	We describe a novel architecture for indoor navigation, based on qualitative representations of the variations in the interactions between the robot and its environment. We use these representations to localize and guide planning and reaction. Off-line, the system accepts as input a topological diagram of the environment. It then uses numerical simulation to generate a map, describing qualitative variations in sensor behavior between adjacent regions in space. An off-line planner stores localized navigation information at each point in the map. During execution, an adaptive controller uses a short-term memory to improve its operation. The qualitative nature of our method, along with the localization performed by the topological planner, result in a compact map representation and in linear-time performances for position estimation and path planning during execution. We have tested this architecture in simulation. Our results show that the proposed navigation method is tolerant of sensor inaccuracies, both in obstacle detection and orientation.	en
heal.publisher	IEEE, Piscataway, NJ, United States	en
heal.journalName	Proceedings - IEEE International Conference on Robotics and Automation	en
dc.identifier.doi	10.1109/ROBOT.1996.503890	en
dc.identifier.volume	1	en
dc.identifier.spage	921	en
dc.identifier.epage	926	en