We present FLISP, a mapless LiDAR-IMU synchronized path planner for cooperative UGV-UAV inspection in large-scale hydropower tunnels. The paper includes field experiments in a 1.2 km operational tunnel and open-source code for reproducibility.</p>\n<p>Code: <a href=\"https://github.com/ArchibaldGuo/FLISP\" rel=\"nofollow\">https://github.com/ArchibaldGuo/FLISP</a><br>Paper: <a href=\"https://arxiv.org/abs/2606.25393\" rel=\"nofollow\">https://arxiv.org/abs/2606.25393</a></p>\n","updatedAt":"2026-06-30T08:28:46.389Z","author":{"_id":"6a40bc89f187d49b7dde3d63","avatarUrl":"/avatars/8f9e893c9077407e0b18a5386cb34ceb.svg","fullname":"Fenghe Guo","name":"ArchibaldGuo","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.8409246802330017},"editors":["ArchibaldGuo"],"editorAvatarUrls":["/avatars/8f9e893c9077407e0b18a5386cb34ceb.svg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2606.25393","authors":[{"_id":"6a40c0750dbbc53604b6684b","user":{"_id":"6a40bc89f187d49b7dde3d63","avatarUrl":"/avatars/8f9e893c9077407e0b18a5386cb34ceb.svg","isPro":false,"fullname":"Fenghe Guo","user":"ArchibaldGuo","type":"user","name":"ArchibaldGuo"},"name":"Fenghe Guo","status":"claimed_verified","statusLastChangedAt":"2026-06-29T13:22:50.629Z","hidden":false},{"_id":"6a40c0750dbbc53604b6684c","name":"Runjie Shen","hidden":false},{"_id":"6a40c0750dbbc53604b6684d","name":"Chenyang Sun","hidden":false},{"_id":"6a40c0750dbbc53604b6684e","name":"Junrui Zhang","hidden":false},{"_id":"6a40c0750dbbc53604b6684f","name":"Quanxi Zhan","hidden":false},{"_id":"6a40c0750dbbc53604b66850","name":"Yongchun Wang","hidden":false},{"_id":"6a40c0750dbbc53604b66851","name":"Junjie Zhang","hidden":false}],"publishedAt":"2026-06-25T00:00:00.000Z","submittedOnDailyAt":"2026-06-30T00:00:00.000Z","title":"Large-Scale Tunnel Air-Ground Collaboration With FLISP: Fast LiDAR-IMU Synchronized Path Planner","submittedOnDailyBy":{"_id":"6a40bc89f187d49b7dde3d63","avatarUrl":"/avatars/8f9e893c9077407e0b18a5386cb34ceb.svg","isPro":false,"fullname":"Fenghe Guo","user":"ArchibaldGuo","type":"user","name":"ArchibaldGuo"},"summary":"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.","upvotes":1,"discussionId":"6a40c0750dbbc53604b66852"},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"6a40bc89f187d49b7dde3d63","avatarUrl":"/avatars/8f9e893c9077407e0b18a5386cb34ceb.svg","isPro":false,"fullname":"Fenghe Guo","user":"ArchibaldGuo","type":"user"}],"acceptLanguages":["en"],"dailyPaperRank":0,"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2606/2606.25393.md","query":{}}">

Get this paper in your agent:

Don't have the latest CLI?

Cite arxiv.org/abs/2606.25393 in a model README.md to link it from this page.

Cite arxiv.org/abs/2606.25393 in a dataset README.md to link it from this page.

Cite arxiv.org/abs/2606.25393 in a Space README.md to link it from this page.

Add this paper to a collection to link it from this page.