Bridging Large-Model Reasoning and Real-Time Control via Agentic Fast-Slow Planning
Large foundation models enable powerful reasoning for autonomous systems, but mapping semantic intent to reliable real-time control remains challenging. Existing approaches either (i) let Large Language Models (LLMs) generate trajectories directly - brittle, hard to verify, and latency-prone - or (ii) adjust Model Predictive Control (MPC) objectives online - mixing slow deliberation with fast control and blurring interfaces. We propose Agentic Fast-Slow Planning, a hierarchical framework that decouples perception, reasoning, planning, and control across natural timescales. The framework contains two bridges. Perception2Decision compresses scenes into ego-centric topologies using an on-veh...
| Authors | Jiayi Chen, Shuai Wang, Guangxu Zhu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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