Robot manipulation in everyday activities with the CRAM 2.0 cognitive architecture and generalized action plans
The CRAM 2.0 robot cognitive architecture provides a framework for knowledge-based instantiation of robot manipulation design patterns for everyday activities. These design patterns take the form of generalized action plans, which are transformed by CRAM 2.0 into parameterized low-level motion plans, using knowledge and reasoning with a contextual model to identify the motion parameter values that will successfully perform the actions required to accomplish the task. In this way, CRAM 2.0 performs implicit-to-explicit manipulation, mapping an under-specified high-level goal to the specific low-level motions required to accomplish the goal. We demonstrate the ability of a CRAM-controlled robot to carry out everyday activities in a kitchen environment.
Authors
- Michael Beetz (ORCID: https://orcid.org/0000-0002-7888-7444)
- Gayane Kazhoyan (ORCID: https://orcid.org/0000-0002-2874-228X)
- David Vernon (ORCID: https://orcid.org/0000-0002-9782-3788)
Institutions
- University of Bremen (DE)
- Carnegie Mellon University Africa (RW)
Publication Details
- Journal
- Cognitive Systems Research
- Published
- 2025-06-21
- DOI
- https://doi.org/10.1016/j.cogsys.2025.101375
- Citations
- 3
- Primary Topic
- AI-based Problem Solving and Planning
- Type
- article
- Field-Weighted Citation Impact
- 7.44
Funders
- Deutsche Forschungsgemeinschaft
- Universität Bremen