摘要
在月面探测过程中,针对月表多不规则地形障碍物(月表陨石凹坑、坡、月岩等)会影响巡视器移动性能以及地面观测者缺少直观的三维的月表环境信息,影响最终决策的问题。文章采用深度(RGB-D)相机获取原始数据,基于三维点云数据进行滤波消噪等处理;再结合机器人越障能力极限与改进的随机采样一致性(Random Sample Consensus,RANSAC)算法,获取其自适应基准平面作为可通行区域;最后使用密度聚类算法(Density-Based Spatial Clustering of Applications with Noise,DBSCAN)提取局部地形障碍物信息,结合基准面进行快速三维场景重建,为地面观测提供直观快速的三维巡视器周围环境模型,并通过模拟月面地形环境试验进行验证。试验结果表明,本文所使用的算法可以有效地获取地形障碍物的空间坐标信息,并进行快速场景重建,大幅度地提高时间效率。可为月面探测任务中,巡视器自主避障以及为地面观测者提供三维视角等提供参考。
During the lunar probe,many irregular terrain obstacles on the lunar surface(meteorite craters,slopes,lunar rocks,etc.)will affect the mobile performance of the rover,and the lack of direct three-dimensional information about the lunar surface environment affects ground observer’s final decision.In this paper,RGB-D camera is used to obtain the original data,and based on 3D point cloud data,noise filtering and other processing is carried out,combined with the obstacle crossing ability limit of the robot and the improved RANSAC(random sample consensus)algorithm,the adaptive reference plane is obtained as the passable region.Finally,DBSCA(density based spatial clustering of applications with noise)algorithm is used to extract local terrain obstacle information,and rapid 3D scene reconstruction is carried out based on the datum,providing an immediate and rapid 3D environment model of the rover for ground observation,which is verified by simulating the lunar terrain environment experiment.Experimental results show that the algorithm used in this paper can effectively obtain the spatial coordinate information of terrain obstacles,and carry out rapid scene reconstruction,improving greatly the time efficiency.It can provide a reference for the rover to avoid obstacles and provide the ground observer with three-dimensional view.
作者
赵迪
戴志鹏
李世其
纪合超
何宁
ZHAO Di;DAI Zhipeng;LI Shiqi;JI Hechao;HE Ning(Hubei University of Technology,Wuhan 430068,China;Huazhong University of Science and Technology,Wuhan 430074,China;China Astronaut Research and Training Centre,Beijing 100094,China)
出处
《航天器工程》
CSCD
北大核心
2019年第5期32-38,共7页
Spacecraft Engineering
基金
国家重大科技专项工程(060601)
