| dc.contributor.author | Braun, T. | |
| dc.date | 2011-05-01 | |
| dc.date.accessioned | 2018-01-08T09:15:04Z | |
| dc.date.available | 2018-01-08T09:15:04Z | |
| dc.date.issued | 2011 | |
| dc.identifier.issn | 1610-1987 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/11209 | |
| dc.description.abstract | The thesis “Cost-Efficient Global Robot Navigation in Rugged Off-Road Terrain” proposes a global robot navigation concept for rugged off-road terrain which is robust against inaccurate self-localization and scalable to large environments, but also cost-conscious, e.g. able to generate navigation paths which optimize a cost measure closely related to terrain traversability. The thesis contributes a set of new techniques to integrate cost-consciousness into a primarily topological navigation scheme. Also, novel methods to learn and optimize cost estimates from experience are developed. | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 25, No. 2 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.subject | Robot navigation | |
| dc.subject | Topological map | |
| dc.subject | Traversability cost learning | |
| dc.title | Cost-Efficient Global Robot Navigation in Rugged Off-Road Terrain | |
| dc.type | Text/Journal Article | |
| mci.reference.pages | 173-177 | |
| gi.identifier.doi | 10.1007/s13218-011-0088-9 | |
