MIRA-PRM：面向移动气体传感检测的任务知情可复用路线图规划
MIRA-PRM: Mission-Informed Reusable Roadmap Planning for Mobile Gas-Sensing Inspection
- Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）
- University of Chinese Academy of Sciences（中国科学院大学）
- Nanjing University of Science and Technology（南京理工大学）
- Nanjing Normal University（南京师范大学）
- North University of China（中北大学）
- University of Glasgow（格拉斯哥大学）
- Universiti Malaysia Perlis（马来西亚玻璃市大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对移动气体传感检测，提出任务知情概率路线图MIRA-PRM，通过多条件采样与局部修复实现高可靠规划，在有限节点下成功率显著优于PRM和PRM*。
AI中文摘要：
移动气体传感检测要求移动平台可靠地到达有序的采样位姿。我们提出了MIRA-PRM，一种任务知情的概率路线图，它将几何、任务流和检测条件采样的采样策略与局部自适应连通性和证据门控细化相结合。八个开发活动共包含142,448次规划器运行，评估了任务规模、重复查询适应性、有限节点预算、目标分布、局部地图修复、消融实验、跨系列比较和参数敏感性。当有序目标从两个增加到八个时，MIRA-PRM保持了100%的种子级成功率，并在40个节点的上限下实现了97.67%的种子级成功率，而PRM为67.17%，PRM*为86.50%。相对于重建，局部修复将事件时间减少了79.9%-81.9%，节点添加减少了90.8%-94.3%。在一个单独的冻结保留集上，包含12张地图、48个有序任务和每个地图-任务单元三个种子，MIRA-PRM产生了96/144个验证成功，而PRM为82/144，PRM*为89/144，LE-HG-PRM为70/144。在配对的共同成功运行中，MIRA-PRM相对于PRM*将墙钟时间减少了16.89%，相对于LE-HG-PRM减少了81.01%，但比PRM慢52.23%；路径长度增加了0.54%-1.86%。所有验证路径均通过了独立的完整段检查和间隙非劣效性检验。结果支持在结构化模拟中进行面向可靠性的权衡，并激励了外部地图和物理移动传感验证。
英文摘要：
Mobile gas-sensing inspection requires a mobile platform to reliably reach ordered sampling poses. We present MIRA-PRM, a mission-informed probabilistic roadmap that combines geometry-, mission-flow-, and inspection-conditioned sampling with locally adaptive connectivity and evidence-gated refinement. Eight development campaigns comprising 142,448 planner runs evaluated mission scaling, repeated-query adaptation, finite node budgets, target distributions, local map repair, ablation, cross-family comparison, and parameter sensitivity. MIRA-PRM maintained 100% seed-level success as ordered targets increased from two to eight, and achieved 97.67% seed-level success under a 40-node ceiling, compared with 67.17% for PRM and 86.50% for PRM*. Local repair reduced event time by 79.9-81.9% and node additions by 90.8-94.3% relative to rebuilding. On a separate frozen holdout of 12 maps, 48 ordered missions, and three seeds per map-mission unit, MIRA-PRM produced 96/144 validated successes, versus 82/144 for PRM, 89/144 for PRM*, and 70/144 for LE-HG-PRM. On paired common-success runs, MIRA-PRM reduced wall time by 16.89% relative to PRM* and 81.01% relative to LE-HG-PRM, but was 52.23% slower than PRM; paths were 0.54-1.86% longer. All validated paths passed independent full-segment checks and clearance non-inferiority. The results support a reliability-oriented trade-off in structured simulations and motivate external-map and physical mobile-sensing validation.
