STMA: A Spatio-Temporal Memory Agent for Long-Horizon Embodied Task Planning

• URL: http://arxiv.org/abs/2502.10177v1
• Date: Fri, 14 Feb 2025 14:12:09 GMT
• Title: STMA: A Spatio-Temporal Memory Agent for Long-Horizon Embodied Task Planning
• Authors: Mingcong Lei, Yiming Zhao, Ge Wang, Zhixin Mai, Shuguang Cui, Yatong Han, Jinke Ren,
• Abstract summary: We propose the S-Temporal Memory Agent (STMA), a framework designed to enhance planning and execution by integratingtemporal memory.<n>We evaluate STMA in theTextWorld environment on 32 tasks, involving multi-step planning and exploration under complexity levels of4.7%.<n> Experimental results demonstrate that STMA achieves a 31.25% success rate and a 24.7% increase in average score compared to the state-of-the-art model.
• Score: 36.70014527951141
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: A key objective of embodied intelligence is enabling agents to perform long-horizon tasks in dynamic environments while maintaining robust decision-making and adaptability. To achieve this goal, we propose the Spatio-Temporal Memory Agent (STMA), a novel framework designed to enhance task planning and execution by integrating spatio-temporal memory. STMA is built upon three critical components: (1) a spatio-temporal memory module that captures historical and environmental changes in real time, (2) a dynamic knowledge graph that facilitates adaptive spatial reasoning, and (3) a planner-critic mechanism that iteratively refines task strategies. We evaluate STMA in the TextWorld environment on 32 tasks, involving multi-step planning and exploration under varying levels of complexity. Experimental results demonstrate that STMA achieves a 31.25% improvement in success rate and a 24.7% increase in average score compared to the state-of-the-art model. The results highlight the effectiveness of spatio-temporal memory in advancing the memory capabilities of embodied agents.

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