基于姿態(tài)測量模塊和閉環(huán)檢測算法的仿生SLAM研究
發(fā)布時間：2018-10-12 11:42
【摘要】：基于傳感器模型的SLAM導航策略精度較高,但由于摩擦等因素誤差長時間累計會造成里程計的漂移現(xiàn)象。依靠視覺里程計進行導航的Rat SLAM系統(tǒng),通過在局部場景細胞中引入閉環(huán)檢測策略實現(xiàn)累計誤差的校正,在靜態(tài)環(huán)境下具有一定的魯棒性,但在復雜場景里,如移動障礙物的出現(xiàn),視覺里程計會提取到錯誤的速度等姿態(tài)信息,導致航跡出現(xiàn)較大偏移,有時無法通過場景重定位進行閉環(huán)校正。結合兩種模型的優(yōu)勢提出一種帶姿態(tài)測量模塊和閉環(huán)檢測算法的仿生SLAM模型。實驗表明,相較于僅帶帶閉環(huán)檢測的Rat SLAM系統(tǒng)或僅由姿態(tài)測量模塊構成的導航系統(tǒng),本文提出的新系統(tǒng)更能適應長期復雜場景下的導航,且魯棒性更強。
[Abstract]:The precision of SLAM navigation strategy based on sensor model is high, but the drift of mileage will be caused by the accumulated error of friction and other factors for a long time. The Rat SLAM system which is guided by vision odometer can correct the cumulative error by introducing closed-loop detection strategy into the cells of local scene. It is robust in static environment, but in complex scene. For example the appearance of moving obstacle the visual mileage meter will extract the wrong attitude information such as velocity and so on which leads to a large deviation of the track and sometimes can not be corrected by the scene re-location closed loop. Combining the advantages of the two models, a bionic SLAM model with attitude measurement module and closed loop detection algorithm is proposed. The experimental results show that the proposed new system is more robust than the Rat SLAM system with closed loop detection or the navigation system composed of attitude measurement modules.
【作者單位】： 安徽工程大學安徽省電氣傳動與控制重點實驗室;
【基金】：2016年安徽高校自然科學研究項目(KJ2016A794) 2016安徽工程大學研究生實踐與創(chuàng)新基金項目(Y040116004)
【分類號】：TP212;TP242
[Abstract]:The precision of SLAM navigation strategy based on sensor model is high, but the drift of mileage will be caused by the accumulated error of friction and other factors for a long time. The Rat SLAM system which is guided by vision odometer can correct the cumulative error by introducing closed-loop detection strategy into the cells of local scene. It is robust in static environment, but in complex scene. For example the appearance of moving obstacle the visual mileage meter will extract the wrong attitude information such as velocity and so on which leads to a large deviation of the track and sometimes can not be corrected by the scene re-location closed loop. Combining the advantages of the two models, a bionic SLAM model with attitude measurement module and closed loop detection algorithm is proposed. The experimental results show that the proposed new system is more robust than the Rat SLAM system with closed loop detection or the navigation system composed of attitude measurement modules.
【作者單位】： 安徽工程大學安徽省電氣傳動與控制重點實驗室;
【基金】：2016年安徽高校自然科學研究項目(KJ2016A794) 2016安徽工程大學研究生實踐與創(chuàng)新基金項目(Y040116004)
【分類號】：TP212;TP242
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