钢结构建筑探伤机器人刚柔耦合空间位姿解析与实验研究

Spatial Pose Analysis and Experimental Validation of a Rigid-Flexible Coupling Robot for Steel Structure Building Inspection

针对传统钢结构建筑健康监测中存在检测盲区和检测不全面的问题,研究了磁吸附式刚柔耦合柔性探伤机器人并对其控制系统进行了改进.建立了柔性机器人前、后车体位移和姿态运动学数学模型与机器人刚柔耦合结构位姿解算方程,通过惯性测量单元和编码器获取柔性探伤机器人前、后车体实时动态位姿参数,分别采用显性互补滤波器和扩展卡尔曼滤波器解算前、后车体在不同工况中的静态、动态姿态,利用航迹推算算法确定机器人的位置,通过数据融合得到柔性机器人刚柔耦合结构的空间位姿.实验结果表明,扩展卡尔曼滤波算法的动态跟踪性能更好,可为柔性探伤机器人在复杂建筑结构越障运动中提供精确的空间位姿参数.

To overcome the problems of blind zone and incomplete detection in the traditional health monitoring of steel structure building, a rigid-flexible coupling structure inspection robot with magnetic adsorption is studied and its control system is improved. The displacement and attitude kinematics mathematical models of the front and rear bodies of flexible robots and the position and attitude equations of the rigid-flexible coupling structure of the robot are established. The inertial measurement unit and encoder are used to get the real-time dynamic pose parameters of the front and rear bodies of flexible robots, the explicit complementary filter and extended Kalman filter are used respectively to calculate the attitudes of the front and the rear bodies of robots in the dynamic and static working conditions, and the dead reckoning algorithm is used to calculate the robot position. Then, the spatial pose of the rigid-flexible coupling structure of flexible robots is obtained through data fusion. The experimental results show that the extended Kalman filter algorithm provides accurate spatial pose parameters and better dynamic tracking performance for the flexible inspection robot in the obstacle-negotiation movement in complex building structures.