BrainMem: Brain-Inspired Evolving Memory for Embodied Agent Task Planning
Embodied task planning requires agents to execute long-horizon, goal-directed actions in complex 3D environments, where success depends on both immediate perception and accumulated experience across tasks. However, most existing LLM-based planners are stateless and reactive, operating without persistent memory and therefore repeating errors and struggling with spatial or temporal dependencies. We propose BrainMem(Brain-Inspired Evolving Memory), a training-free hierarchical memory system that equips embodied agents with working, episodic, and semantic memory inspired by human cognition. BrainMem continuously transforms interaction histories into structured knowledge graphs and distilled s...
| Authors | Xiaoyu Ma, Lianyu Hu, Wenbing Tang et al. |
|---|---|
| Primary category | cs.RO |
| Published | 12 March 2026 |
| Last updated at source | 12 March 2026 |
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