# A Detailed Guide to 5 Mainstream Robot Path Planning Algorithms: MPC, Reinforcement Learning, Graph Search, and More

- Source: 深蓝AI · 微信公众号
- Published: 2026-10-30T01:48:00.000Z
- RoboHot: https://robohot.news/en/items/nyvjfsmtrfxk2xbuvliupz49l
- Original: https://mp.weixin.qq.com/s?__biz=MzY4NjA5NTgyMQ==&mid=2247606088&idx=1&sn=d2008615e3b8654ef1ca6a8eb93966a4&chksm=f293d8f38f9806ac976242ebb067bc74013df6cc177c3b4f54ade02f924c014db63a33c545de&scene=126&sessionid=1793367016#rd

## Summary

Following the thread of "how to solve problems in different environments," the article reviews five categories of path planning paradigms in embodied intelligence: graph search (Dijkstra, A*, Hybrid A*), sampling methods (RRT, PRM), artificial potential field (APF), optimal control (MPC), and reinforcement learning and data-driven methods.