基于混合滤波算法的灭火机器人设计
|
摘要
为使两轮灭火机器人适应各类复杂的火灾环境,融合互补算法和卡尔曼算法对灭火机器人实时采集到的数据进行滤波处理,结合MATLAB软件建立姿态角计算模型,并对算法进行仿真分析,得到了静态试验数据和动态试验数据,并且对灭火机器人躲避障碍的性能进行了相关测试。研究结果表明,采用融合算法的灭火机器人姿态角能够实现较精确的控制,并较好地躲避障碍物。
In order to adapt the two-wheel fire extinguishing robot to various complex fire environments, study its working principle and its fire extinguishing process characteristics. And combine the complementary algorithm and Kalman algorithm, the real-time moral data collected by the fire extinguishing robot was filtered and processed. The algorithm was simulated and analyzed with MATLAB software. Static test data and dynamic test data were obtained, and the performance of the fire-fighting robot to avoid obstacles was tested. The results showed that the attitude angle of fire-fighting robot using fusion algorithm can achieve more precise control and better avoid obstacles, so it can be applied to the actual fire-fighting process, and can perform various fire-fighting actions stably and accurately.
In order to adapt the two-wheel fire extinguishing robot to various complex fire environments, study its working principle and its fire extinguishing process characteristics. And combine the complementary algorithm and Kalman algorithm, the real-time moral data collected by the fire extinguishing robot was filtered and processed. The algorithm was simulated and analyzed with MATLAB software. Static test data and dynamic test data were obtained, and the performance of the fire-fighting robot to avoid obstacles was tested. The results showed that the attitude angle of fire-fighting robot using fusion algorithm can achieve more precise control and better avoid obstacles, so it can be applied to the actual fire-fighting process, and can perform various fire-fighting actions stably and accurately.
引文
[1]柳倩,桂建军,杨小薇,等.工业机器人传感控制技术研究现状及发展态势--基于专利文献计量分析视角[J].机器人,2016,38(5):612-620.
[2]由韶泽,朱华,赵勇,等.煤矿救灾机器人研究现状及发展方向[J].工矿自动化,2017,43(4):14-18.
[3]李世光,王文文,申梦茜,等.基于变论域模糊PI四轮机器人的仿真与研究[J].科学技术与工程,2016,16(10):29-34.
[4]张战杰.基于直流电机驱动电路的移动式采摘机器人设计[J].农机化研究,2019,(4):23-24.
[5]马茵,田磊,韩孟洋.基于WIFI数字图像传输的采摘机器人交互终端研发[J].农机化研究,2018,40(5):12-14.
[6]张栋,焦嵩鸣,刘延泉.互补滤波和卡尔曼滤波的融合姿态解算方法[J].传感器与微系统,2017,(3):45-47.
[7]陈孟元,谢义建,陈跃东.基于四元数改进型互补滤波的MEMS姿态解算[J].电子测量与仪器学报,2015,29(9):1391-1397.
[8]吕印新,肖前贵,胡寿松.基于四元数互补滤波的无人机姿态解算[J].燕山大学学报,2014,(2):175-180.
[9]万芳,牛树云,朱丽丽,等.基于DSRC与点检测器数据融合的实时交通状态表达方法[J].公路交通科技,2017,(8):10-11.
[10]杨婷,陈德运,王莉莉.一种新颖的电容层析成像数据采集滤波算法[J].哈尔滨理工大学学报,2018,(2):12-17.
[11]何坚,周明我,王晓懿.基于卡尔曼滤波与k-NN算法的可穿戴跌倒检测技术研究[J].电子与信息学报,2017,(11):23-26.
[12]WU J,ZHOU Z,CHEN J,et al.Fast complementary filter for attitude estimation using low-cost MARG sensors[J].IEEE Sensors Journal,2016,16(18):1-1.
[2]由韶泽,朱华,赵勇,等.煤矿救灾机器人研究现状及发展方向[J].工矿自动化,2017,43(4):14-18.
[3]李世光,王文文,申梦茜,等.基于变论域模糊PI四轮机器人的仿真与研究[J].科学技术与工程,2016,16(10):29-34.
[4]张战杰.基于直流电机驱动电路的移动式采摘机器人设计[J].农机化研究,2019,(4):23-24.
[5]马茵,田磊,韩孟洋.基于WIFI数字图像传输的采摘机器人交互终端研发[J].农机化研究,2018,40(5):12-14.
[6]张栋,焦嵩鸣,刘延泉.互补滤波和卡尔曼滤波的融合姿态解算方法[J].传感器与微系统,2017,(3):45-47.
[7]陈孟元,谢义建,陈跃东.基于四元数改进型互补滤波的MEMS姿态解算[J].电子测量与仪器学报,2015,29(9):1391-1397.
[8]吕印新,肖前贵,胡寿松.基于四元数互补滤波的无人机姿态解算[J].燕山大学学报,2014,(2):175-180.
[9]万芳,牛树云,朱丽丽,等.基于DSRC与点检测器数据融合的实时交通状态表达方法[J].公路交通科技,2017,(8):10-11.
[10]杨婷,陈德运,王莉莉.一种新颖的电容层析成像数据采集滤波算法[J].哈尔滨理工大学学报,2018,(2):12-17.
[11]何坚,周明我,王晓懿.基于卡尔曼滤波与k-NN算法的可穿戴跌倒检测技术研究[J].电子与信息学报,2017,(11):23-26.
[12]WU J,ZHOU Z,CHEN J,et al.Fast complementary filter for attitude estimation using low-cost MARG sensors[J].IEEE Sensors Journal,2016,16(18):1-1.