2 papers
cs.AI2025
Proposition of Affordance-Driven Environment Recognition Framework Using Symbol Networks in Large Language Models
Kazuma Arii, Satoshi Kurihara
In the quest to enable robots to coexist with humans, understanding dynamic situations and selecting appropriate actions based on common sense and affordances are essential. Conven…
cs.AI2025
LLM-mediated Dynamic Plan Generation with a Multi-Agent Approach
Reo Abe, Akifumi Ito, Kanata Takayasu +1
Planning methods with high adaptability to dynamic environments are crucial for the development of autonomous and versatile robots. We propose a method for leveraging a large langu…