FLTRNN: Faithful Long-Horizon Task Planning for Robotics with Large Language Models
Jiatao Zhang,Lanling Tang,Yufan Song,Qiwei Meng,Haofu Qian,Jun Shao,Wei Song,Shiqiang Zhu,Jason Gu,Jiatao Zhang,Lanling Tang,Yufan Song,Qiwei Meng,Haofu Qian,Jun Shao,Wei Song,Shiqiang Zhu,Jason Gu
Recent planning methods based on Large Language Models typically employ the In-Context Learning paradigm. Complex long-horizon planning tasks require more context(including instructions and demonstrations) to guarantee that the generated plan can be executed correctly. However, in such conditions, LLMs may overlook(unfaithful) the rules in the given context, resulting in the generated plans being ...
