arXiv 2610.28589 · cs.RO · 2026-10-20
AgenticRoboRL: Bringing Coding-Agent Post-Training to Agentic Robotics
Xinxin Liu, Bingxin Xu, Wenrui Bao, Ming Li, Wentao Bao, Chen Chen, Yuzhang Shang
University of Central Florida
在最新榜 #244 本站收录于 2026-10-24
一句话要点
中佛罗里达大学的 AgenticRoboRL 把编程智能体的后训练思路搬到机器人规划器上：不再只靠闭源大模型加更好的执行框架，而是直接后训练规划器本身，并兼容 VLA 技能调用和控制代码生成等不同执行方式。
UCF's AgenticRoboRL brings coding-agent-style post-training to robot planners: instead of relying on closed models plus better harnesses, it post-trains the planner itself across harnesses with different execution mechanisms, including VLA skill invocation and control-code generation.
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数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-26。
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