遮挡感知、准静态、面向稳定性的不平地形轨迹规划
Occlusion-Aware, Quasi-Static, Stability-Oriented Trajectory Planning on Uneven Terrain
- University of Tartu（塔尔图大学）
- IIIT Hyderabad（印度海得拉巴国际信息技术学院）
- Czech Technical University（捷克理工大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对不平地形上的四轮车辆，提出遮挡感知的准静态稳定性轨迹规划框架，通过不确定性传播与流匹配热启动，将失败率降至18.9%。
AI中文摘要：
在非结构化越野环境中的自主导航需要同时考虑车辆与地形的相互作用以及环境未知性。我们提出了一种基于模型的框架，用于在高度不平的地形上为刚性、非铰接的四轮车辆生成准静态、面向稳定性的参考轨迹。我们的工作有三项主要贡献。首先，我们将由地形遮挡引起的盲区建模为固定特征傅里叶地形表示中的覆盖诱导认知不确定性，并通过正则化逆黑塞矩阵估计进行量化。其次，我们通过隐式微分将此不确定性传播到非线性最小二乘（NLS）位姿/接触模型中，并将由此产生的位姿、接触点和每个车轮的表面法向不确定性项纳入基于交叉熵方法（CEM）的轨迹优化中。第三，我们引入了一个流匹配模型来热启动地形拟合，并在保留基于模型的细化的情况下评估其拟合精度与延迟的权衡。在六个合成地形上，每个地形有30对匹配的起点-终点对，完整框架的观测失败率为18.9%，而两个代表性基线的失败率分别为46.1%和41.7%，去除传播不确定性评分的消融实验的失败率为34.4%。硬件评估涵盖六个不同的户外环境，论文中展示了两次代表性执行，另外四次执行包含在补充视频中。评估还报告了流匹配热启动的精度-延迟权衡。
英文摘要：
Autonomous navigation in unstructured off-road environments requires reasoning about both vehicle--terrain interaction and environmental unknowns. We propose a model-based framework for generating quasi-static, stability-oriented reference trajectories for rigid, non-articulated four-wheeled vehicles on highly uneven terrain. Our work makes three primary contributions. First, we model blind spots caused by terrain occlusion as coverage-induced epistemic uncertainty in a fixed-feature Fourier terrain representation, quantified through a regularized inverse-Hessian estimate. Second, we propagate this uncertainty through the Nonlinear Least-Squares (NLS) pose/contact model using implicit differentiation and incorporate the resulting pose, contact-point, and per-wheel surface-normal uncertainty terms into trajectory optimization based on the Cross-Entropy Method (CEM). Third, we introduce a Flow Matching model that warm-starts terrain fitting, and we evaluate its fitting-accuracy--latency trade-off while retaining model-based refinement. Across six synthetic terrains with 30 matched start--goal pairs per terrain, the complete framework produced an observed failure rate of 18.9%, compared with 46.1% and 41.7% for two representative baselines and 34.4% for an ablation that removed the propagated-uncertainty scoring. Hardware evaluations span six distinct outdoor environments, with two representative executions presented in the paper and four additional executions included in the supplementary video. The evaluation also reports the accuracy--latency trade-off for the Flow Matching warm start.
