发表机构
Toronto Metropolitan University; University College London（多伦多都会大学; 伦敦大学学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
H-SPAR提出一种水动力感知仿真框架，集成流场、粒子输运与USV自主性，实验显示电流感知规划在执行中优势下降，且扫描方向显著影响采样率，强调联合评估的重要性。
AI 中文摘要
环境机器人采样需要考虑水流对机器人运动和粒子输运的双重影响。现有的海洋机器人仿真器通常分别对水流、自主性和采样目标进行建模，限制了任务成本和采样性能的联合评估。H-SPAR集成了时空变化的流速场、拉格朗日粒子输运、概率采样以及基于ROS 2/Gazebo的无人水面艇（USV）自主性。在本工作中，共享的预计算流场在闭环车辆执行过程中驱动粒子平流和电流引起的力。路径规划实验表明，现有的电流感知规划器SVF-RRT*在规划层面比传统RRT*的上游成本降低了69.4%，但在时变水流下的执行过程中，这一降低幅度降至41.7%，反映了规划中忽略的时间流变化、车辆运动约束和路径偏差。覆盖实验表明，在完整的H-SPAR配置下，扫描方向会改变粒子采样率高达22.2%。这些发现强调了在一致的水动力条件下联合评估规划、车辆执行、粒子输运和采样的重要性。项目网页可在https://this URL访问，开源代码可在GitHub上获取：https://this URL。
英文摘要
Environmental robotic sampling requires considering the dual influence of water currents on robotic motion and particle transport. Existing marine robotics simulators generally model flow, autonomy, and sampling targets separately, limiting joint evaluation of mission cost and sampling performance. H-SPAR integrates spatially and temporally varying velocity fields, Lagrangian particle transport, probabilistic sampling, and ROS 2/Gazebo-based uncrewed surface vehicle (USV) autonomy. In this work, shared precomputed flow fields drive particle advection and current-induced forces during closed-loop vehicle execution. Path-planning experiments show that the existing current-aware planner SVF-RRT* achieves 69.4% lower upstream cost than conventional RRT* at the planning level, but this reduction falls to 41.7% during execution under time-varying currents, reflecting temporal flow variation, vehicle motion constraints, and path deviation omitted during planning. Coverage experiments show that sweep orientation changes the particle-sampling rate by up to 22.2% under the complete H-SPAR configuration. These findings highlight the importance of evaluating planning, vehicle execution, particle transport, and sampling together under consistent hydrodynamic conditions. The project webpage is available at https://sites.google.com/view/h-spar, and the open-source code is available on GitHub at https://github.com/naviiidz/h-spar-sim.
Comments20 pages, 4 Figures, 3 Tables
