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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2505.19339 |
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| _version_ | 1866912393224781824 |
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| author | Wang, Libo |
| author_facet | Wang, Libo |
| contents | To address the gaps between the static pre-set "thinking-planning-action" of humanoid robots in unfamiliar scenarios and the highly programmed "call tool-return result" due to the lack of autonomous coding capabilities, this work designs a dynamic architecture connecting continuous thought machines (CTM) and model context protocol (MCP). It proposes a theoretical parallel solution through tick-slab and uses rank compression to achieve parameter suppression to provide a solution for achieving autonomous actions due to autonomous coding. The researcher used a simulation-based experiment using OpenAI's o4-mini-high as a tool to build the experimental environment, and introduced the extended SayCan dataset to conduct nine epochs of experiments. The experimental results show that the CTM-MCP architecture is feasible and effective through the data results of seven metrics: task success rate (TSR), execution success rate (ESR), average episode length (AEL), ROSCOE, REVEAL, proficiency self-assessment (PSA), task effectiveness (TE). In practice, it provides a reference experience for exploring the autonomous dynamic coding of humanoid robots based on continuous thinking to achieve human-like autonomous actions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_19339 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Humanoid Robot Autonomy: A Dynamic Architecture Integrating Continuous thought Machines (CTM) and Model Context Protocol (MCP) Wang, Libo Robotics Artificial Intelligence To address the gaps between the static pre-set "thinking-planning-action" of humanoid robots in unfamiliar scenarios and the highly programmed "call tool-return result" due to the lack of autonomous coding capabilities, this work designs a dynamic architecture connecting continuous thought machines (CTM) and model context protocol (MCP). It proposes a theoretical parallel solution through tick-slab and uses rank compression to achieve parameter suppression to provide a solution for achieving autonomous actions due to autonomous coding. The researcher used a simulation-based experiment using OpenAI's o4-mini-high as a tool to build the experimental environment, and introduced the extended SayCan dataset to conduct nine epochs of experiments. The experimental results show that the CTM-MCP architecture is feasible and effective through the data results of seven metrics: task success rate (TSR), execution success rate (ESR), average episode length (AEL), ROSCOE, REVEAL, proficiency self-assessment (PSA), task effectiveness (TE). In practice, it provides a reference experience for exploring the autonomous dynamic coding of humanoid robots based on continuous thinking to achieve human-like autonomous actions. |
| title | Towards Humanoid Robot Autonomy: A Dynamic Architecture Integrating Continuous thought Machines (CTM) and Model Context Protocol (MCP) |
| topic | Robotics Artificial Intelligence |
| url | https://arxiv.org/abs/2505.19339 |