Mental Models for Intelligent Systems: eRobotics Enables New Approaches to Simulation-Based AI
| dc.contributor.author | Roßmann, Jürgen | |
| dc.contributor.author | Guiffo Kaigom, Eric | |
| dc.contributor.author | Atorf, Linus | |
| dc.contributor.author | Rast, Malte | |
| dc.contributor.author | Grinshpun, Georgij | |
| dc.contributor.author | Schlette, Christian | |
| dc.date.accessioned | 2018-01-08T09:17:09Z | |
| dc.date.available | 2018-01-08T09:17:09Z | |
| dc.date.issued | 2014 | |
| dc.description.abstract | eRobotics is a newly evolving branch of e-Systems engineering, providing tools to support the whole life cycle of robotic applications by means of electronic media. With the eRobotics methodology, the target system and its environment can be modeled, validated, and calibrated to achieve a close-to-reality simulation. In this contribution, we present simulation-based mental models for autonomous systems as a foundation for new approaches to prediction and artificial intelligence. We formulate a methodology to construct optimization problems within simulation environments in order to assist autonomous systems in action planning. We illustrate the usefulness and performance of this approach through various examples in different fields. As application for space robotics, we focus on climbing strategies of a legged mobile exploration robot. Furthermore, we enable skillfull interaction control in service robotics and address energy consumption issues. The contribution concludes with a detailed discussion of the concept presented here. | |
| dc.identifier.pissn | 1610-1987 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/11400 | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 28, No. 2 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.subject | Actuation and Control | |
| dc.subject | eRobotics | |
| dc.subject | Optimization | |
| dc.subject | Simulation-based AI | |
| dc.title | Mental Models for Intelligent Systems: eRobotics Enables New Approaches to Simulation-Based AI | |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 110 | |
| gi.citation.startPage | 101 |