摘要
二维激光测距仪辅助惯性导航系统、视觉系统等实现机器人或微小型飞行器定位需要解决的关键问题是扫描匹配。本文对已有的RS/LS,IDC,Cox以及ICP等扫描匹配算法进行改进,提出一种R-I-C组合策略。根据扫描中提取线段的情况选择性使用Cox算法和IDC算法,由基于留点的ICP算法或RS/LS算法为其提供可靠的初始估计。该组合策略既适用于多边形环境,也适用于非多边形环境,具有一定智能性,能够处理大变换,定位精确度高。本文采用仿真比较R-I-C组合策略和上述常用匹配算法,并采用三轴转台和一维激光测距仪模拟二维激光测距仪,用R-I-C算法对实验数据进行计算。仿真结果表明该组合策略定位误差可达5%以下,而计算速度不超过1 s。
The-key-problem-of-using-the-two-dimensional-laser-range-finder-as-an-assistant-of-Inertial-Navigation-System-and-Visual-System-for-robot-and/or-Micro-Air-Vehicle-positioning-is-laser-scan-matching.-The-exiting-RS/LS-algorithm,-Iterative-Dual-Correspondence(IDC)-algorithm,-Cox-algorithm-and-Iterative-Closest-Point(ICP)-algorithm,-are-improved-by-adopting-a-combination-strategy-called-R-I-C.-The-choosing-of-the-Cox-algorithm-and-the-IDC-algorithm-depends-on-line-extracting.-The-residual-point-based-ICP-algorithm-and/or-the-Rotation-Search/Least-Squares(RS/LS)-algorithm-can-provide-an-initial-estimation-for-the-Cox-or-IDC-algorithm.-This-combination-strategy-can-be-used-on-both-polygon-and-un-polygon-environments-with-certain-intelligence,large-transform-capability-and-high-positioning-accuracy.-R-I-C-combination-algorithm-is-compared-with-the-common-matching-algorithms-mentioned-above-by-simulation.-A-three-axis-turntable-and-one-dimensional-laser-range-finder-are-employed-to-simulate-the-two-dimensional-laser-range-finder,and-the-data-is-processed-by-R-I-C-combination-algorithm.-The-results-indicate-that-the-error-of-R-I-C-is-below-5%,-and-the-cost-of-time-is-less-than-one-second.
出处
《太赫兹科学与电子信息学报》
2014年第4期549-553,共5页
Journal of Terahertz Science and Electronic Information Technology
关键词
激光测距仪
扫描匹配
组合策略
laser range finder
scan matching
combination strategy