Environment perception method based on PSO for Multi-millimeter wave security robot
Security robots frequently operate in the severe environments with dim and smoke,etc.Such an environment can be detected using millimeter wave,but its point cloud is sparse.Correspondingly the multi-millimeter waves point clouds can be fused to improve the ability to perceive environment.Accurate structural parameters are required for point cloud fusion to address the error in obtaining structural parameters through measurement.By analyzing the coordinates of multi-millimeter wave point cloud,particle swarm algorithm is utilized to search the structural parameters of millimeter wave radar,and the point cloud fusion as well as the construction of environment map are carried out according to the search results.Simultaneously,the evaluation critical of sparse point cloud map is proposed to quantitatively assess the millimeter wave sensing effect.Experiments were carried out in a darkened environment with a security robot,the results of which are as follows.The number of point clouds increases.The number of map boundary holes decreases by 55%on average.The boundary noise rate is reduced by 12.9%on average.The dispersion of the object point clouds decreases by about 0.06 on average.There is a decrease in the offsets of center positions in all experiments,when compared to the multi-millimeter-wave perception system where the structural parameters were obtained by the measurement method.
FM millimeter-wavesecurity robotPSOenvironmental perceptionmapping
NETL
NSTL
万方数据
