SCAN-Planner: Spatial Collision-Aware Local Planning for Route-Guided Long-Range Quadruped Navigation

• URL: http://arxiv.org/abs/2606.19555v1
• Date: Wed, 17 Jun 2026 19:55:09 GMT
• Title: SCAN-Planner: Spatial Collision-Aware Local Planning for Route-Guided Long-Range Quadruped Navigation
• Abstract summary: SCAN-Planner is a spatial collision-aware local planning framework for long-range quadruped navigation.<n>A yaw-aware twin-cylinder footprint is used to model the elongated robot body.<n>For large-scale deployment, a robot-centric sliding map with boundary fallback provides high-resolution local collision checking.
• Score: 9.033597184884746
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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