外观
论文arXiv 2608.161642 个月前
非结构化地形上足式运动的轨迹级自动课程学习
原文链接：Trajectory-Level Automatic Curriculum Learning for Legged Locomotion on Unstructured Terrain（arXiv 2608.16164 · 发布日期：2026-08-17）
Trajectory-Level Automatic Curriculum Learning for Legged Locomotion on Unstructured Terrain
该文针对非结构化地形足式运动课程设计困难，提出轨迹级自动课程学习框架，并在非结构化地形轨迹任务上验证成功率提升。
核心要点
- 非结构化地形缺少显式难度排序，启发式参数化课程易限制泛化。
- 框架直接从地形图生成轨迹任务，用评估器学习当前策略的任务难度函数。
- 采样器依据评估器提出新轨迹，与策略更新形成闭环匹配课程。
- 实验显示较无课程直接训练成功率提升56.3%，较手工课程在困难任务和多方向接近评估中更高。
验证范围与局限：验证范围为摘要所述非结构化地形轨迹任务，未说明仿真或真机平台。
英文摘要 (Abstract)
Training locomotion policies for complex unstructured terrain requires a curriculum to avoid early exploration failures. However, since unstructured terrain lacks explicit difficulty ordering for curriculum design, existing methods resort to heuristic curricula over parameterized terrains. This abstraction limits generalization, as policies can overadapt to near-fixed perceptual patterns. To address this, we propose \textbf{\ourname{}}, an \textbf{T}rajectory-level \textbf{A}utomatic \textbf{C}urriculum \textbf{L}earning framework that generates training tasks directly from unstructured terrain maps. At each curriculum update, the evaluator learns a difficulty function for the current policy that maps a given trajectory task to a difficulty score. The sampler then proposes new trajectories guided by the learned evaluator as the curriculum for the next policy update. This forms a closed loop in which the curriculum is iteratively matched to the evolving policy. Quantitative and qualitative experiments show that \ourname{} continuously provides effective curricula on unstructured terrain, improving trajectory success rate by (56.3%) over direct training without curriculum. Compared with handcrafted curriculum learning, our method improves success rate by (18.5%) on the hardest terrain tasks and by up to (39.74%) when evaluating traversal from diverse approach directions on the same obstacle type.
作者：Rocky Liu, Tengyu Liu, Baoxiong Jia, Fangwei Zhong, Xinyi Tong, Hongzhao Xie, Siyuan Huang
来源
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