Projects per year
Abstract
Much prior work in integrating high-level artificial intelligence planning technology with low-level robotic control has foundered on the significant representational differences between these two areas of research. We discuss a proposed solution to this representational discontinuity in the form of object-action complexes (OACs). The pairing of actions and objects in a single interface representation captures the needs of both reasoning levels, and will enable machine learning of high-level action representations from low-level control representations.
Original language | English |
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Title of host publication | IEEE-RAS Humanoids-06 Workshop: Towards Cognitive Humanoid Robots |
Number of pages | 6 |
Publication status | Published - 2006 |
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Dive into the research topics of 'Object Action Complexes as an Interface for Planning and Robot Control'. Together they form a unique fingerprint.Projects
- 1 Finished
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Xperience - 'Robotes Bootstrapped through Learning from Experience'
Steedman, M., Geib, C. & Petrick, R.
1/01/10 → 31/12/15
Project: Research