混合地形感知路径规划：整合VD-RRT*探索与VD-D* Lite修复
摘要
在离岸环境中运行的自动地面车辆必须在实时内规划出考虑空间变化土壤强度和坡度危险的曲率可行路径。我们提出了一种连续状态-成本度量，将Bekker压力-沉埋模型与由坡度和姿态衍生的惩罚相结合。 resulting terrain cost field is analytic, bounded, and monotonic in soil modulus and slope, ensuring well-posed discretization and stable updates under sensor noise. This metric is evaluated on a lattice with exact steering primitives: Dubins and Reeds--Shepp motions for differential drive and time-parameterized bicycle arcs for Ackermann steering. Global exploration is performed using Vehicle-Dynamics RRT, while local repair is managed by Vehicle-Dynamics D Lite, enabling millisecond-scale replanning without heuristic smoothing. By separating the terrain--vehicle model from the planner, the framework provides a reusable basis for deterministic, sampling-based, or learning-driven planning in deformable terrain. Hardware trials on an off-road platform demonstrate real-time navigation across soft soil and slope transitions, supporting reliable autonomy in unstructured environments.
引用
@article{arxiv.2510.12169,
title = {Hybrid Terrain-Aware Path Planning: Integrating VD-RRT* Exploration and VD-D* Lite Repair},
author = {Akshay Naik and William R. Norris and Dustin Nottage and Ahmet Soylemezoglu},
journal= {arXiv preprint arXiv:2510.12169},
year = {2025}
}