Multi-Scenario Reasoning: Unlocking Cognitive Autonomy in Humanoid Robots for Multimodal Understanding

• URL: http://arxiv.org/abs/2412.20429v3
• Date: Tue, 07 Jan 2025 18:24:45 GMT
• Title: Multi-Scenario Reasoning: Unlocking Cognitive Autonomy in Humanoid Robots for Multimodal Understanding
• Authors: Libo Wang,
• Abstract summary: This research proposes a multi-scenario reasoning architecture to solve the technical shortcomings of multi-modal understanding in this field.<n>The findings demonstrate the feasibility of this architecture in multimodal data.<n>It heralds the future development of self-learning and autonomous behavior of humanoid robots in changing scenarios.
• Score: 4.586907225774023
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: To improve the cognitive autonomy of humanoid robots, this research proposes a multi-scenario reasoning architecture to solve the technical shortcomings of multi-modal understanding in this field. It draws on simulation based experimental design that adopts multi-modal synthesis (visual, auditory, tactile) and builds a simulator "Maha" to perform the experiment. The findings demonstrate the feasibility of this architecture in multimodal data. It provides reference experience for the exploration of cross-modal interaction strategies for humanoid robots in dynamic environments. In addition, multi-scenario reasoning simulates the high-level reasoning mechanism of the human brain to humanoid robots at the cognitive level. This new concept promotes cross-scenario practical task transfer and semantic-driven action planning. It heralds the future development of self-learning and autonomous behavior of humanoid robots in changing scenarios.

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