---
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id: "1f7bfb882534fbf4171d2ccff107213bbbe452391e3958962ee9cb7fbb14d98b"
canonical_url: "https://aidr.today/1f7bfb88?lang=en"
title: "AgenticRoboRL: Bringing Coding-Agent Post-Training to Agentic Robotics"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-10-22T00:00:00.000Z"
category: "Frameworks"
topics: ["agent","framework"]
source_urls: ["https://huggingface.co/papers/2610.28589"]
summary: "AgenticRoboRL is a framework for post-training robot planners across different harnesses. It combines supervised fine-tuning with multi-turn reinforcement learning and uses harness-specific adapters to connect planner interactions with task outcomes."
---

# AgenticRoboRL: Bringing Coding\-Agent Post\-Training to Agentic Robotics

> [Open the canonical story](<https://aidr.today/1f7bfb88?lang=en>)

**Published:** 2026-10-22T00:00:00.000Z
**Category:** Frameworks
**Topics:** agent, framework

## Summary

AgenticRoboRL is a framework for post\-training robot planners across different harnesses\. It combines supervised fine\-tuning with multi\-turn reinforcement learning and uses harness\-specific adapters to connect planner interactions with task outcomes\.

## Sources

- [Story source](<https://huggingface.co/papers/2610.28589>)