Simultaneous Localization and Mapping Technology Based on Project Tango

最新推荐文章于 2024-08-09 10:39:42 发布

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最新推荐文章于 2024-08-09 10:39:42 发布

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原文链接：http://www.cnblogs.com/2008nmj/p/10556639.html

针对同步定位与地图构建（SLAM）技术中系统误差和噪声问题，提出基于Project Tango设备的校准模型和基于带内存管理视觉词汇的回环检测算法，结合图优化实现运行应用。通过收集环境信息建立校准模型，计算匹配特征，求解运动姿态模型，实验表明该算法可行且高效。

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Abstract: Aiming at the problem of system error and noise in simultaneous localization and mapping (SLAM) technology, we propose a calibration model based on Project Tango device and a loop closure detection algorithm based on visual vocabulary with memory management. The graph optimization is also combined to achieve a running application. First, the color image and depth information of the environment are collected to establish the cali- bration model of system error and noise. Second, with constraint condition provided by loop closure detection algorithm, speed up robust feature is calculated and matched. Finally, the motion pose model is solved, and the optimal scene model is determined by graph optimization method. This method is compared with Open Constructor for reconstruction on several experimental scenarios. The results show the number of model’s points and faces are larger than Open Constructor’s, and the scanning time is less than Open Constructor’s. The experimental results show the feasibility and efficiency of the proposed algorithm.

转载于:https://www.cnblogs.com/2008nmj/p/10556639.html