构建可扩展的垂直复杂地形自动驾驶评测基准，支持多车型与真实交互测试。
Verti-Bench: A General and Scalable Off-Road Mobility Benchmark for Vertically Challenging Terrain
- 基于高保真多物理仿真，设计100个独特越野环境和1000项导航任务。
- 涵盖数百万种地形属性，包含刚性/柔性表面及大型自然障碍物，支持动态交互评估。
- 适用于强化学习、专家示范等研究，适合越野机器人与自主系统开发者使用。
近年来，户外非结构化环境中的自主移动机器人发展迅速，模拟与实测均取得积极成果。然而，相较于静态数据集上的感知任务评测，越野机动性评估仍面临诸多挑战，如车辆平台差异与地形特性变化。此外，机动性评估需动态交互环境，而非依赖预采集数据。本文提出Verti-Bench，一个专注于极端崎岖、垂直挑战性地形的机动性评测基准。该基准包含100个独特的越野环境、1000项不同的导航任务，以及数百万种地形属性，涵盖多种几何与语义特征、刚性与可变形表面及大型自然障碍物，实现高保真多物理仿真下的标准化客观评估。Verti-Bench可扩展至不同尺寸与驱动机制的车辆平台。我们还提供了专家示范、随机探索、失败案例（翻车、卡住）数据集，以及类Gym接口用于强化学习。利用Verti-Bench，我们对十套越野机动系统进行了评测，呈现结果并指明未来研究方向。
原文摘要 · Abstract (English)
Recent advancement in off-road autonomy has shown promises in deploying autonomous mobile robots in outdoor off-road environments. Encouraging results have been reported from both simulated and real-world experiments. However, unlike evaluating off-road perception tasks on static datasets, benchmarking off-road mobility still faces significant challenges due to a variety of factors, including variations in vehicle platforms and terrain properties. Furthermore, different vehicle-terrain interactions need to be unfolded during mobility evaluation, which requires the mobility systems to interact with the environments instead of comparing against a pre-collected dataset. In this paper, we present Verti-Bench, a mobility benchmark that focuses on extremely rugged, vertically challenging off-road environments. 100 unique off-road environments and 1000 distinct navigation tasks with millions of off-road terrain properties, including a variety of geometry and semantics, rigid and deformable surfaces, and large natural obstacles, provide standardized and objective evaluation in high-fidelity multi-physics simulation. Verti-Bench is also scalable to various vehicle platforms with different scales and actuation mechanisms. We also provide datasets from expert demonstration, random exploration, failure cases (rolling over and getting stuck), as well as a gym-like interface for reinforcement learning. We use Verti-Bench to benchmark ten off-road mobility systems, present our findings, and identify future off-road mobility research directions.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。