Draft:Cognitive robotic abstract machine
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Submission declined on 18 June 2026 by Helpful Raccoon (talk). This draft appears to contain text generated by a large language model (such as ChatGPT). You cannot use LLMs to generate article content.
Declined by Helpful Raccoon 2 months ago.LLM-generated pages with certain obvious signs of being machine generated may be deleted without notice. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. See the advice page on large language models for more information. | |
Submission declined on 23 April 2026 by ChrysGalley (talk). This draft appears to contain text generated by a large language model (such as ChatGPT). You cannot use LLMs to generate article content.
LLM-generated pages with certain obvious signs of being machine generated may be deleted without notice. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. See the advice page on large language models for more information.This draft's references do not show that the subject meets Wikipedia's criteria for inclusion. The draft requires multiple published secondary sources that:
Declined by ChrysGalley 4 months ago.
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Comment: I will take a look at this. 16dvnk (talk) 09:32, 29 August 2026 (UTC)- Comment: Sources provided are all primary. Axolitl (talk | contribs) 04:32, 29 August 2026 (UTC)
- Comment: Vague and superficial analysis such as
The framework has been cited in research related to knowledge-enabled robotics, semantic reasoning, robot planning, and autonomous service robots
(added after the previous LLM decline) is characteristic of LLM usage; please remove all text from the draft and start over from a blank slate without LLMs. Helpful Raccoon (talk) 03:23, 18 June 2026 (UTC)
- Comment: Notability requires multiple sources giving in-depth coverage, see the WP:GOLDENRULE. We aren't here to promote just one essay. I think this is AI assisted since the paper is obviously online and the reference here is offline.... Plus the language used is AI-ish. ChrysGalley (talk) 08:32, 23 April 2026 (UTC)
Cognitive Robot Abstract Machine (CRAM) is a cognitive architecture for autonomous robots designed to perform everyday manipulation tasks in human environments.[1][2] It was developed by Beetz et al. at the University of Bremen. It claims to let robots transform underspecified task instructions into context‑sensitive and executable actions.[3] This is based on its current beliefs about the environment and the predicted outcomes of actions.[3]
Description
[edit]CRAM is a hybrid cognitive architecture that integrates symbolic and sub‑symbolic representations and processes.[3] It can achieve this by transforming underspecified abstract task instructions into context‑sensitive executable actions.[1]
The architecture connects symbolic knowledge directly to both the robot's perception and movement systems and to the internal data structures that govern its behavior.[4] The core of the system is built around two primary elements, which are the CPL plan language and the KnowRob knowledge processing framework.[4][5]
History
[edit]Beetz et al. introduced CRAM at the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), where they described it as a software toolbox for cognition‑enabled robotics.[1] It has been extended with features like semantic digital twins, episodic memory systems, and dual‑process reasoning.[3] The second generation, CRAM 2.0, was developed as part of a German Research Foundation (DFG) project and was introduced in a 2025 article in the journal Cognitive Systems Research.[6][7]
Architecture
[edit]CRAM is a cognitive architecture that employs generalized action plans.[3] They are transformed into parameterized low‑level motion plans using knowledge and reasoning with a contextual model.[6] Process modules can be configured by the higher‑level control logic. These modules interpret the properties of designators and convert them into specific low‑level commands based on the robot's current understanding of its environment.[4][1]
KnowRob is a knowledge processing system that delivers reasoning and knowledge services for autonomous robots.[4] Its modular design can allow components to be loaded only when required.[4]
Applications
[edit]CRAM has been used in research on cognition‑enabled robot control, including mobile manipulation in household environments.[1][8] The CRAM cognitive architecture allows a robot to carry out activities such as laying a table for a meal and loading a dishwasher afterward.[2]
Differences between other architectures
[edit]CRAM is one of several cognitive architectures for robotics.[3][9] According to Beetz and Kümpel et al., its core feature was its emphasis on lightweight reasoning.[3] A 2025 study by Beetz et al. on CRAM 2.0 shows that the architecture addresses underdetermined task specification through generalized action plans that are instantiated via contextual queries to a semantic knowledge base.[6]
See also
[edit]References
[edit]- 1 2 3 4 5 Beetz, Michael; Mösenlechner, Lorenz; Tenorth, Moritz (2010). "CRAM – A Cognitive Robot Abstract Machine for Everyday Manipulation in Human Environments". IEEE/RSJ International Conference on Intelligent Robots and Systems. pp. 1012–1017. doi:10.1109/IROS.2010.5650146.
- 1 2 Vernon, David (2022). "Action Selection and Execution in Everyday Activities: A Cognitive Robotics and Situation Model Perspective". Topics in Cognitive Science. 14 (2): 344–362. doi:10.1111/tops.12569. PMID 34459566.
- 1 2 3 4 5 6 7 Beetz, Michael; Kümpel, Michaela (2026). "From Frames to Pouring: The CRAM Cognitive Architecture for Everyday Robot Manipulation". KI – Künstliche Intelligenz. doi:10.1007/s13218-026-00917-z.
- 1 2 3 4 5 "CRAM Cognitive Robot Abstract Machine". University of Bremen. Retrieved 2026-08-29.
- ↑ Vernon, David (2022). "Cognitive Architectures" (PDF). Cognitive Robotics. MIT Press. pp. 191–212.
- 1 2 3 Beetz, Michael; Kazhoyan, Gayane; Vernon, David (2025). "Robot manipulation in everyday activities with the CRAM 2.0 cognitive architecture and generalized action plans". Cognitive Systems Research. 92 101375. doi:10.1016/j.cogsys.2025.101375.
- ↑ "CRAM 2.0 — 2. Generation einer kognitiven Architektur für die Ausführung von alltäglichen Manipulationsaufgaben". GEPRIS. German Research Foundation. Retrieved 2026-08-29.
- ↑ Evaluation of Cognitive Architectures: SASE vs. CRAM (Report). Karlsruhe Institute of Technology. 2024.
- ↑ Reip, Michael (2016). Dependable Belief Management for High-Level Robot Programs (PDF) (Master's thesis). Graz University of Technology.
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