Journal of Jilin University(Engineering and Technology Edition) ›› 2020, Vol. 50 ›› Issue (5): 1850-1855.doi: 10.13229/j.cnki.jdxbgxb20190806

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Component awareness adaptive model based on attitude estimation algorithms

Nai-yan GUAN1,2(),Juan-li GUO1,2   

  1. 1.School of Architecture, Tianjin University, Tianjin 300072, China
    2.Key Laboratory of Building Physical Environment and Ecological Technology, Tianjin University, Tianjin 300072, China
  • Received:2019-07-19 Online:2020-09-01 Published:2020-09-16

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Abstract:

The traditional adaptive models are constructed by geometric optics method, geometric similarity method and feature target measurement method. There exist some problems in such model, such as long perception delay and low accuracy of adaptive tracking. To overcome these problems, a component perception adaptive model based on attitude estimation algorithm is proposed. The model consists of three parts. Firstly, the sensor component is calibrated by using Zhang Zhengyou's camera calibration method based on planar template. Then, the three-dimensional model of the target object is established to track the moving object. Finally, the real-time attitude state of the target object is calculated by using the model-based attitude estimation method to realize the construction of the component perception adaptive model. Experimental results show that compared with the three traditional models mentioned above, the adaptive control of the proposed model can shorten the sensing delay of components, improve the adaptive tracking accuracy and improve the operation performance of the manipulator.

Key words: computer application, attitude estimation algorithm, components, perception, adaptive model

CLC Number: 

  • TP391

Fig.1

Schematic diagram of Zhang Zheng-you camera calibration method based on plane template"

Fig.2

Image coordinate system"

Fig.3

3D model diagram of manipulator structure"

Fig.4

Attitude estimation process of target object"

Fig.5

Experimental test platform"

Table 1

Model perceptual delay results"

组件感知 自适应模型姿态估计算法

几何

光学法

几何

相似法

特征靶标测量法
抬起状态0.120.270.340.17
抓取状态0.250.300.330.15
放置状态0.180.250.230.29
返回状态0.250.280.210.33
总体延时0.801.101.110.94

Fig.6

Attitude adaptive accuracy test"

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