中国机械工程
中國機械工程
중국궤계공정
CHINA MECHANICAl ENGINEERING
2011年
24期
2927-2930
,共4页
移动机器人%同步定位与建图%扩展Kalman滤波器%直线特征
移動機器人%同步定位與建圖%擴展Kalman濾波器%直線特徵
이동궤기인%동보정위여건도%확전Kalman려파기%직선특정
mobile robot%simultaneous localization and mapping（SLAM）%extended Kalman filter（EKF）%line feature
针对移动机器人的同步定位与建图（SLAM）问题,提出了一种基于改进的扩展Kalman滤波算法的同步定位与建图方法。通过建立基于直线特征提取的机器人观测模型,推导了SLAM建图的预测和更新算式,设计了基于特征点数目的SLAM预测与更新率算子,实现了移动机器人的同步定位与建图。实验结果表明该方法有效、可行。
針對移動機器人的同步定位與建圖（SLAM）問題,提齣瞭一種基于改進的擴展Kalman濾波算法的同步定位與建圖方法。通過建立基于直線特徵提取的機器人觀測模型,推導瞭SLAM建圖的預測和更新算式,設計瞭基于特徵點數目的SLAM預測與更新率算子,實現瞭移動機器人的同步定位與建圖。實驗結果錶明該方法有效、可行。
침대이동궤기인적동보정위여건도（SLAM）문제,제출료일충기우개진적확전Kalman려파산법적동보정위여건도방법。통과건립기우직선특정제취적궤기인관측모형,추도료SLAM건도적예측화경신산식,설계료기우특정점수목적SLAM예측여경신솔산자,실현료이동궤기인적동보정위여건도。실험결과표명해방법유효、가행。
For mobile robot simultaneous localization and mapping（SLAM） key issues,an improved SLAM method based on extended Kalman filter was presented.Through the establishment of the observation model based on line features,the prediction and state-updating of the SLAM were formulated,the computing cycles were designed based on the number of feature points and the simultaneous localization and mapping were realized.Experimental results show that the method is effective and feasible.
