用手机投影网格感知地面起伏，提升小车越障稳定性。
Terrain Sensing with Smartphone Structured Light: 2D Dynamic Time Warping for Grid Pattern Matching
- 提出2D-DTW算法，按列对齐变形网格，保持结构一致性。
- 可在资源受限设备运行，实现高精度地形重建。
- 适用于手机投影测距、图像网格匹配等场景。
低成本移动机器人常在不平整地形上运行，微小凸起或倾斜难以通过视觉察觉，却严重影响运动稳定性。为此，本文探索基于智能手机的结构光系统，通过投影网格到地面，仅用单个手持设备重建局部地形起伏。该系统受人脸识别投影器启发，但针对地面感知进行改进。关键挑战在于在透视畸变和部分遮挡下，鲁棒匹配投影网格与观测变形图案。传统一维动态时间规整（1D-DTW）不适用于二维网格。因此，本文提出拓扑约束的二维动态时间规整（2D-DTW）算法，在全局网格一致性约束下进行列方向对齐。该方法设计简洁，可运行于资源受限平台，同时保留三角测量所需的网格结构。实验表明，所提2D-DTW不仅可用于地形感知，还可作为通用图像处理中结构化网格匹配工具。本文详述系统设计及由此衍生的2D-DTW扩展。
原文摘要 · Abstract (English)
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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