# ABot-AgentOS: A General Robotic Agent OS with Lifelong Multi-modal Memory

Page: https://stenobird.com/podcast/daily-paper-cast-7079649/abot-agentos-a-general-robotic-agent-os-with-lifelong-multi-modal-memory
Text version: https://stenobird.com/podcast/daily-paper-cast-7079649/abot-agentos-a-general-robotic-agent-os-with-lifelong-multi-modal-memory.md
Podcast: [Daily Paper Cast](https://stenobird.com/podcast/daily-paper-cast-7079649)
Published: 2026-07-15T03:36:42+00:00
Episode link: https://share.transistor.fm/s/dad85862
Audio file: https://media.transistor.fm/dad85862/42fd21e9.mp3
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JSON: https://stenobird.com/v1/public/podcasts/daily-paper-cast-7079649/episodes/abot-agentos-a-general-robotic-agent-os-with-lifelong-multi-modal-memory
Duration seconds: 1338

## Resource

🤗 Upvotes: 68 | cs.AI, cs.RO Authors: Jiayi Tian, Shiao Liu, Yuting Xu, Jia Lu, Zihao Guan, Honglin Han, Di Yang, Minqi Gu, Yifei Qian, Tianlin Zhang, Yanqing Zhu, Zeqian Ye, Menglin Yang, Fei Wang, Xu Hu, Xiuxian Li, Wei Zhang, Shihui Su, Yiyan Ji, Jingbo Wang, Ziteng Feng, Jiaheng Liu, Zhaoxiang Zhang, Xiaolong Wu, Mingyang Yin, Zedong Chu, Mu Xu Title: ABot-AgentOS: A General Robotic Agent OS with Lifelong Multi-modal Memory Arxiv: http://arxiv.org/abs/2607.10350v1 Abstract: Recent VLM and VLA systems have improved robotic perception and action prediction, yet long-horizon embodied agents still require a general runtime layer for reasoning, memory, tool use, verification, and cross-embodiment execution. We present ABot-AgentOS, a general robotic Agent Operating System that sits above low-level controllers and provides a deliberative agent layer for scene-conditioned planning, context-isolated skill execution, multi-stage verification, multi-modal memory, and edge-cloud collaboration. To evaluate such systems, we introduce EmbodiedWorldBench, an executable benchmark with 16 indoor, outdoor, and hybrid scenes, four difficulty levels, and over 200 tasks involving navigation, object search, NPC dialogue, dynamic events, and trace-grounded scoring. ABot-AgentOS further introduces Universal Multi-modal Graph Memory, a persistent source-grounded substrate that converts dialogue, visual observations, spatial context, temporal relations, and task traces into typed nodes and edges. A failure-driven self-evolution loop converts diagnosed memory failures into gated runtime evo-assets that are promoted only to later evaluation splits, preventing current-split ground-truth leakage while enabling continual improvement. On an initial EmbodiedWorldBench subset, ABot-AgentOS improves…

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