The STRANDS project: Long-term autonomy in everyday environments
Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Repr...
Egile Nagusiak: | Hawes, N, Burbridge, C, Jovan, F, Kunze, L, Lacerda, B, Mudrova, L, Young, J, Wyatt, J, Hebessberger, D, Kortner, T, Ambrus, R, Bore, N, Folkesson, J, Jensfelt, P, Beyer, L, Hermans, A, Leibe, B, Aldoma, A, Faulhammer, T, Zillich, M, Vincze, M, Chinellato, E, Al-Omari, M, Duckworth, P, Gatsoulis, Y, Hogg, D, Cohn, A, Dondrup, C, Fentanes, J, Krajnik, T, Santos, J, Duckett, T, Hanheide, M |
---|---|
Formatua: | Journal article |
Argitaratua: |
IEEE
2017
|
Antzeko izenburuak
-
Autonomous learning of object models on a mobile robot
nork: Faulhammer, T, et al.
Argitaratua: (2016) -
Artificial intelligence for long-term robot autonomy: A survey
nork: Kunze, L, et al.
Argitaratua: (2018) -
SOMA: a framework for understanding change in everyday environments using Semantic Object Maps
nork: Kunze, L, et al.
Argitaratua: (2018) -
Unsupervised learning of qualitative motion behaviours by a mobile robotUnsupervised learning of qualitative motion behaviours by a mobile robot
nork: Duckworth, P, et al.
Argitaratua: (2016) -
Making sense of indoor spaces using semantic web mining and situated robot perception
nork: Young, J, et al.
Argitaratua: (2017)