Towards locally computable polynomial navigation functions for convex obstacle workspaces

Lionis, G; Papageorgiou, X; Kyriakopoulos, KJ

dc.contributor.author	Lionis, G	en
dc.contributor.author	Papageorgiou, X	en
dc.contributor.author	Kyriakopoulos, KJ	en
dc.date.accessioned	2014-03-01T02:45:49Z
dc.date.available	2014-03-01T02:45:49Z
dc.date.issued	2008	en
dc.identifier.issn	10504729	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32414
dc.subject	Computational Complexity	en
dc.subject	Dynamic Environment	en
dc.subject	Local Computation	en
dc.subject	Local Knowledge	en
dc.subject	Motion Planning	en
dc.subject.other	Industrial engineering	en
dc.subject.other	Polynomial approximation	en
dc.subject.other	Polynomials	en
dc.subject.other	Robotics	en
dc.subject.other	International conferences	en
dc.subject.other	Navigation function	en
dc.subject.other	Partial knowledge	en
dc.subject.other	Navigation	en
dc.title	Towards locally computable polynomial navigation functions for convex obstacle workspaces	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ROBOT.2008.4543782	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ROBOT.2008.4543782	en
heal.identifier.secondary	4543782	en
heal.publicationDate	2008	en
heal.abstract	In this paper we present a polynomial Navigation Function (NF) for a sphere world that can be constructed almost locally, with partial knowledge of the environment. The presented navigation function is C2 and as a result the computational complexity is very low, while the construction uses local knowledge and information. Moreover, an almost locally computable diffeomorphism between convex obstacles and spheres is presented, allowing the NF scheme to be used in a workspace populated by convex obstacles. Our approach is not strictly local in the ε sense, i.e. the field around a point is not influenced only by an ε region around the point, but rather it is local in the sense that the NF around each obstacle is influenced only by the obstacle and the adjacent obstacles. In particular, we require, in the vicinity of an obstacle, the distance between the obstacle and the adjacent obstacles. Simulations are presented to verify this approach. ©2008 IEEE.	en
heal.journalName	Proceedings - IEEE International Conference on Robotics and Automation	en
dc.identifier.doi	10.1109/ROBOT.2008.4543782	en
dc.identifier.spage	3725	en
dc.identifier.epage	3730	en