An ontology-based multi-level robot architecture for learning from experiences S Rockel, B Neumann, J Zhang, SKR Dubba, AG Cohn, S Konecny, ... 2013 AAAI Spring Symposium Series, 2013 | 50 | 2013 |
Online task merging with a hierarchical hybrid task planner for mobile service robots S Stock, M Mansouri, F Pecora, J Hertzberg 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 41 | 2015 |
The RACE project: Robustness by autonomous competence enhancement J Hertzberg, J Zhang, L Zhang, S Rockel, B Neumann, J Lehmann, ... KI-Künstliche Intelligenz 28, 297-304, 2014 | 29 | 2014 |
Planning domain+ execution semantics: a way towards robust execution S Konecný, S Stock, F Pecora, A Saffiotti Qualitative Representations for Robots, AAAI Spring Symposium, 2014 | 24 | 2014 |
Hierarchical hybrid planning in a mobile service robot S Stock, M Mansouri, F Pecora, J Hertzberg KI 2015: Advances in Artificial Intelligence: 38th Annual German Conference …, 2015 | 17 | 2015 |
Integrating physics-based prediction with semantic plan execution monitoring S Rockel, Š Konečný, S Stock, J Hertzberg, F Pecora, J Zhang 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 11 | 2015 |
Generating and executing hierarchical mobile manipulation plans S Stock, M Guenther, J Hertzberg ISR/Robotik 2014; 41st International Symposium on Robotics, 1-6, 2014 | 7 | 2014 |
Hierarchische hybride Planung für mobile Roboter S Stock Institut für Informatik, Universität Osnabrück, 2017 | 4 | 2017 |
Hierarchical hybrid planning for mobile robots S Stock KI-Künstliche Intelligenz 31 (4), 373-376, 2017 | 3 | 2017 |
Towards a flexible hybrid planner for machine coordination in arable farming S Stock, K Lingemann, S Stiene, J Hertzberg Informatik in der Land-, Forst-und Ernährungswirtschaft 2016, 2016 | 2 | 2016 |
Towards Contextual Robots for Collaborative Manufacturing J de Gea Fernández, D Mronga, M Günther, S Stock, N Niemann, ... | | |
4.20 Towards an Integrated Hierarchical Planner for Complex Robot Tasks S Stock Robots Learning from Experiences, 99, 0 | | |