大规模隧道空地协同中的FLISP：快速LiDAR-IMU同步路径规划器

摘要

水工隧洞检测对基础设施完整性至关重要，但采用人工方法时效率低下且存在安全隐患。本文提出FLISP（快速激光雷达-惯性测量单元同步路径规划器），这是一种用于UGV-UAV协同检测的无地图规划框架。与传统基于地图的范式不同，FLISP具有三项核心贡献：（1）统一架构，通过单一UGV搭载的LiDAR-IMU套件驱动两平台同步路径生成；（2）特定平台求解器，采用改进萤火虫算法实现UGV避障，并采用动态迭代优化器规划UAV飞行路径；（3）分层优化策略，在无状态估计漂移前提下确保运动学可行性。在1.2公里运营隧道的基准测试中，FLISP规避了基于地图方法的结构性瓶颈，消除了地图栅格化开销（Fast-LIO2 + A*）和采样不稳定性（LIO-SAM + RRT*）。FLISP达到100%成功率，延迟仅7毫秒，较基于栅格的方法实现7倍加速，较基于采样的基线方法提升三个数量级。经实际运营水工隧洞验证，该方法为退化特征的线性基础设施机器人检测提供了可扩展解决方案。演示视频见https://youtu.be/Y_ezs1PfLJ4，代码见https://github.com/ArchibaldGuo/FLISP.git。

English

Hydropower tunnel inspection is critical for infrastructure integrity yet remains inefficient and hazardous using manual methods. We propose FLISP (Fast LiDAR-IMU Synchronized Path Planner), a mapless planning framework for cooperative UGV-UAV inspection. Unlike traditional map-based paradigms, FLISP features three core contributions: (1) a unified architecture where a single UGV-mounted LiDAR-IMU suite drives synchronized path generation for both platforms; (2) platform-specific solvers utilizing an enhanced Firefly Algorithm for UGV obstacle avoidance and a dynamic iterative optimizer for UAV flight; and (3) a hierarchical refinement strategy ensuring kinematic feasibility without state estimation drift. Benchmarks in a 1.2 km operational tunnel demonstrate that FLISP circumvents structural bottlenecks of map-based methods, eliminating map rasterization overhead (Fast-LIO2 + A*) and sampling instability (LIO-SAM + RRT*). FLISP achieves a 100% success rate with 7 ms latency, representing a 7-fold speedup over grid-based and a three-order-of-magnitude improvement over sampling-based baselines. Validated in operational hydropower tunnels, this approach offers a scalable solution for robotic inspection in feature-degraded linear infrastructure. A demonstration video is available at https://youtu.be/Y_ezs1PfLJ4, and the code at https://github.com/ArchibaldGuo/FLISP.git.