SCAN-Planner: 経路誘導型長距離四足歩行ナビゲーションのための空間衝突認識ローカルプランナー
SCAN-Planner: Spatial Collision-Aware Local Planning for Route-Guided Long-Range Quadruped Navigation
四足ロボットの長距離ナビゲーション向けに、ヨー角を考慮したツインシリンダーフットプリントと投影A*探索を用いた空間衝突認識ローカルプランニングフレームワークを提案し、狭い通路や3D非構造環境での安全で効率的な移動を実現した。
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著者: Han Zheng, Zhe Chen, Yiwen Fu, Ming Yang, Tong Qin
分類: cs.RO
原文アブストラクト
Quadruped robots are increasingly expected to navigate through narrow passages, cluttered indoor scenes, and large-scale 3D unstructured environments. Existing local planners commonly approximate the robot using isotropic geometric inflation or rely on planar and elevation-map representations, leading to conservative motion in tight spaces and limited reasoning about overhanging structures. This letter presents SCAN-Planner, a spatial collision-aware local planning framework for long-range quadruped navigation. A yaw-aware twin-cylinder footprint is used to model the elongated robot body, enabling whole-body collision evaluation through sparse queries in an inflated 3D occupancy map. We further introduce a projected A* search that generates collision-free guidance on an interpolated ground-following surface, with z-gradient suppression to avoid obstacles horizontally while maintaining vertical stability. For large-scale deployment, a robot-centric sliding map with boundary fallback provides high-resolution local collision checking and recovery from local dead ends. Simulation and real-world experiments demonstrate that SCAN-Planner generates safe, smooth, and efficient trajectories in dense clutter, 3D unstructured scenes, stair traversal, and long-range navigation tasks.
