Precise perception method for position and posture of hydraulic supports based on multi-sensor fusion
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摘要:
为精确感知扰动环境下液压支架位姿信息，提出了一种基于多传感器融合的液压支架位姿精确感知方法。首先，在液压支架顶梁、掩护梁、后连杆和底座4个构件上部署九轴姿态传感器，利用其陀螺仪、加速度计和磁力计分别解算出其所在构件的横滚角、俯仰角和偏航角等位姿数据；然后，通过无迹卡尔曼滤波（UKF）算法和梯度下降（IGD）算法（IGD−UKF算法）对位姿数据进行滤波处理，降低扰动因素对位姿数据的干扰；最后，采用自适应加权融合算法对滤波处理后的液压支架顶梁和底座的偏航角和横滚角数据进行融合处理，消除外界振动、噪声等因素引起的液压支架顶梁和底座传感器数据误差。对施加扰动下液压支架顶梁低头和抬头、底座低头和抬头、液压支架左倾和右倾、液压支架左偏和右偏等工况下顶梁、掩护梁、后连杆和底座的位姿进行感知实验，结果表明：经IGD−UKF算法处理后的数据曲线波动趋于平缓，在抑制振荡、减小振幅上的效果明显；液压支架偏航角误差为0.001 8～0.025 1°，平均绝对误差为0.004 8°，横滚角误差为0.001 4～0.028 1°，平均绝对误差为0.004 7°，实现了扰动环境下液压支架位姿的精确感知。
Abstract:This study aims to accurately perceive the position and posture information of hydraulic supports in a disturbed environment. To address this, a precise perception method for the position and posture of hydraulic supports based on multi-sensor fusion was proposed. Firstly, nine-axis attitude sensors were deployed on four components of the hydraulic support, including top beam, shield beam, rear linkage, and base, to measure roll, pitch, and yaw angles using gyroscopes, accelerometers, and magnetometers. Then, the position and posture data was filtered using the Unscented Kalman Filter (UKF) algorithm and Improved Gradient Descent (IGD) algorithm (IGD-UKF algorithm), reducing interference from disturbance factors. Finally, an adaptive weighted fusion algorithm was employed to merge the filtered yaw and roll angle data of the top beam and base of hydraulic supports, eliminating data deviations caused by external vibrations, noise, and other factors. Perception experiments were conducted on the position and posture of top beam, shield beam, rear linkage, and base under various working conditions. The disturbances included the lowering and raising of top beam and base, as well as left-leaning, right-leaning, left-deviating and right-deviating of hydraulic supports. The study found that the data curves processed by the IGD-UKF algorithm exhibited smoother fluctuations, significantly suppressing oscillations and reducing amplitude. The yaw angle error of hydraulic supports ranged from 0.001 8° to 0.025 1°, with an average absolute error of 0.004 8°. The roll angle error ranged from 0.001 4° to 0.028 1°, with an average absolute error of 0.004 7°. The results indicate that the precise perception of the position and posture of hydraulic supports in a disturbed environment is achieved.
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图 1 液压支架支护位姿精确感知流程
Figure 1. Precise perception process for position and posture of hydraulic supports
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图 5 液压支架位姿感知实验平台
Figure 5. Experimental platform for position and posture perception of hydraulic supports
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图 6 UKF与IGD−UKF滤波效果对比
Figure 6. Comparison of filtering effects between UKF and IGD-UKF
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图 7 液压支架顶梁与底座姿态角融合前后效果对比
Figure 7. Comparison of effects before and after fusion of attitude angles of top beam and base of hydraulic supports
表 1 自适应加权融合算法融合位姿数据误差结果
Table 1 Error results of position and posture data fused by adaptive weighted fusion algorithm
（°） 液压支架姿态角 最小误差 最大误差 平均绝对误差 偏航角 0.001 8 0.025 1 0.004 8 横滚角 0.001 4 0.028 1 0.004 7 
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