利用智能手机结构光进行地形感知：基于二维动态时间变形的网格匹配
Terrain Sensing with Smartphone Structured Light: 2D Dynamic Time Warping for Grid Pattern Matching
AI总结：
本文提出一种基于智能手机的结构光系统，利用二维动态时间变形算法实现地形感知和网格匹配。
摘要：
低成本的移动探测器通常在不平整的地形上运行，其中小的起伏或倾斜难以通过视觉感知，但会显著影响运动稳定性。为了解决这个问题，我们探索了一种基于智能手机的结构光系统，该系统将网格图案投影到地面上，并通过单个手持设备重建局部地形不平整。该系统受到人脸识别投影器的启发，但适用于地面感知。一个关键的技术挑战是稳健地匹配投影的网格与其变形的观测，以应对透视畸变和部分遮挡。传统的单维动态时间变形（1D-DTW）不能直接应用于这种二维网格图案。因此，我们提出了一种拓扑约束的二维动态时间变形（2D-DTW）算法，该算法在全局网格一致性约束下进行列向对齐。所提出的方法设计为能够在资源受限的平台上运行，同时保持用于准确三角化的网格结构。我们证明了所提出的2D-DTW公式不仅可用于地形感知，还可作为图像处理场景中匹配结构化网格图案的一般工具。本文描述了整体系统设计以及由此应用产生的2D-DTW扩展。
英文摘要：
Low-cost mobile rovers often operate on uneven terrain where small bumps or tilts are difficult to perceive visually but can significantly affect locomotion stability. To address this problem, we explore a smartphone-based structured-light system that projects a grid pattern onto the ground and reconstructs local terrain unevenness from a single handheld device. The system is inspired by face-recognition projectors, but adapted for ground sensing. A key technical challenge is robustly matching the projected grid with its deformed observation under perspective distortion and partial occlusion. Conventional one-dimensional dynamic time warping (1D-DTW) is not directly applicable to such two-dimensional grid patterns. We therefore propose a topology-constrained two-dimensional dynamic time warping (2D-DTW) algorithm that performs column-wise alignment under a global grid consistency constraint. The proposed method is designed to be simple enough to run on resource limited platforms while preserving the grid structure required for accurate triangulation. We demonstrate that our 2D-DTW formulation can be used not only for terrain sensing but also as a general tool for matching structured grid patterns in image processing scenarios. This paper describes the overall system design as well as the 2D-DTW extension that emerged from this application.
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