多传感器点云数据融合算法环境感知研究OA

To improve the perception accuracy of indoor mobile robots towards static and dynamic obstacles,this paper proposes a multi-sensor point cloud data fusion algorithm.Firstly,the depth camera data is converted into a point cloud,and an ultrasonic data point cloud transformation algorithm is proposed to extend one-dimensional acoustic data into two-dimensional point clouds;Subsequently,laser radar,camera,and ultrasonic point cloud are integrated to form a unified environmental representation.Experiments have shown that compared to a single LiDAR,this algorithm reduces the relative error of detecting hollow and transparent static obstacles by 94.64%and 95.04%,respectively,and reduces the error of detecting dynamic obstacles by 84.32%,significantly improving the accuracy of environmental perception.