基于地形特征时频变换的无人特种车辆速度自适应控制方法

To ensure the safety, autonomy, and mobility of unmanned special vehicles in complex environments, a speed-adaptive control method based on terrain feature time-frequency transform is proposed for navigating the unmanned special vehicles on rugged terrains. The autonomy and adaptive speed planning of unmanned special vehicles on rugged terrains is achieved by measuring the ruggedness of terrain and establishing a continuous mathematical model of terrain ruggedness and vehicle speed. The point cloud data is corrected through the fusion of inertial measurement unit (IMU) sensor data. This correction ensures the precision of the point cloud data in front of the vehicle, addressing the issues arising from rocky terrain and slopes. Subsequently, a line-to-surface approach is employed to quantify the ruggedness across various terrains, which is diferent from the traditional transverse curvature calculation. The ruggedness value is determined by choosing the integrated area of the sub-frequency region in the frequency domain after the time-frequency transformation of LIDAR longitudinal profile point cloud data. Moreover, a mathematical model for speed and terrain ruggedness is established through an iterative search based on the quantified ruggedness values. The ruggedness value is continuously updated using a sliding window, facilitating the seamless mapping between vehicle speed and terrain ruggedness. The proposed method is then validated utilizing a seismic vibrator vehicle as the research subject through a series of experiments conducted in actual field terrain environments. The experimental results affirm the effectiveness of the proposed method in terrain identification and adaptive vehicle speed control.