Abstract: Abstract: Spray target detection is one of critical steps in variable-rate spray applications. Laser sensor scanning technologies have been used to detect spray targets for precision variable-rate sprayers due to its high accuracy, rapid scan speed, and insensitivity to light sources. However, potential uneven road conditions could reduce detection accuracy of object scanning with laser sensor. In order to obtain accurate shapes of laser scanning targets and acquire three-dimensional (3-D) reconstruction images under complex terrain conditions, an indoor target detection platform with a laser sensor scanner was built to conduct spray target detection experiments under simulated uneven road conditions, and 3 correction methods were proposed to correct laser scanning data distortion due to the influence of complex field conditions. The target laser scanning detection platform consisted of a slide motion control unit and a laser sensor data collection unit. The slide motion control unit was able to control laser travel speed and laser moving distance on the sliding table. The laser sensor data collection unit was capable of detecting spray targets with the laser scanner and saving laser data for post process. The changes of attitude angles of laser sensor in 3 directions including pitch angle, roll angle and yaw angle were used to simulate complex terrain during field operations. Three data correction methods were proposed to diminish the influence caused by attitude angle deviations. They were the methods of re-matching polar coordinate value and trigonometric function for pitch angle deviation correction, re-combination of detection frames and detection points for roll angle deviation correction, and correcting the coefficient value of depth data for yaw angle deviation correction, respectively. The verification experiments for the proposed 3 correction methods to overcome complex field road conditions were divided into 3 test steps. Firstly, an artificial tree and a tree-shape carved board were detected with zero attitude angle deviation of laser sensor by specifying constant detection distances and laser travel speeds. Secondly, the tree-shape carved board was selected as the laser scanning target to test each deviation correction method of single attitude angle. Six angle values including -30o, -20o, -10o, 10o, 20o, and 30o were chosen for roll angle to simulate single uneven road conditions. So were angle values setting for pitch angle and yam angle. Finally, the artificial tree was selected as the laser scanning test target to verify the effectiveness of the combined attitude angle deviation correction. Three groups of combined attitude angle deviations were selected to simulate complex road conditions and to test the correction effects under the combinations of roll angle, pitch angle and yaw angle. All of acquired laser scanning object data were analyzed and corrected by the 3 proposed data correction algorithms. The data correction process and 3-D image reconstruction were conducted using Matlab software. The experiment results showed the spray object scanning with laser sensor could achieve precise outline shape detection of targets and obtain accurate 3-D reconstruction images when the laser sensor had not attitude angle deviations and the target detection test platform was under ideal and flat road environments. The relative errors of the height, width and canopy height of tree-shape carved board were all less than 5.0% by using the deviation correction method of single attitude angle to overcome simulated uneven road conditions. The relative errors of the corresponding parameters of the artificial tree were all less than 10.0% by using the deviation correction method of combined attitude angle to decrease the influence of complex uneven road conditions. The 3-D reconstruction images also had significant improvements after the correction algorithms. The test results verified the effectiveness of the 3 data correction methods for attitude angle deviation correction under simulated complex road conditions. The proposed methods have the potential to be integrated into variable-rate sprayers for precise spray field applications.