An autonomous vehicle operates in a dynamically changing environment,where multiple sensors must work in a cooperative mode. In these scenarios reliability of the communication protocol carries a lot of importance in ...An autonomous vehicle operates in a dynamically changing environment,where multiple sensors must work in a cooperative mode. In these scenarios reliability of the communication protocol carries a lot of importance in real time data transfer. In this paper, CAN communication is used to demonstrate sensor integration using a LIDAR and a camera. Also demonstrated is a novel method for object detection, obstacle avoidance and navigation of an autonomous RC vehicle.展开更多
航空激光测距技术的发展推动了森林资源调查的技术革新。利用机载激光雷达(Light Detection and Ranging,LiDAR)数据能够精确测量森林结构。结合地面调查样本,LiDAR数据可在大范围内实现高分辨率的森林资源评估。文章以东北地区中8个样...航空激光测距技术的发展推动了森林资源调查的技术革新。利用机载激光雷达(Light Detection and Ranging,LiDAR)数据能够精确测量森林结构。结合地面调查样本,LiDAR数据可在大范围内实现高分辨率的森林资源评估。文章以东北地区中8个样地作为研究对象,使用机载激光雷达点云数据实现对样地内单木林业信息的检核与更新。首先,基于剖面旋转算法,实现样地区域的单木分割。考虑到林业参数与树种的相关性,建立树种与分割树冠几何形态之间的对应关系,实现基于LiDAR数据的树种识别。在已知树种类别的基础上,提取样地内单木树高、冠幅、胸径、地上生物量和蓄积量等森林参数,实现林业参数的检核与更新。实验结果显示,树冠分割F 1分数超过95%,树种识别准确率超过90%,树高、东西冠幅、南北冠幅、胸径、地上生物量及蓄积量的决定系数R^(2)分别为89.3%、75.7%、69.4%、84.0%、89.6%和89.1%。结果表明:激光雷达调查方法实用性强且可以广泛应用于大范围林业精确调查中。展开更多
文摘An autonomous vehicle operates in a dynamically changing environment,where multiple sensors must work in a cooperative mode. In these scenarios reliability of the communication protocol carries a lot of importance in real time data transfer. In this paper, CAN communication is used to demonstrate sensor integration using a LIDAR and a camera. Also demonstrated is a novel method for object detection, obstacle avoidance and navigation of an autonomous RC vehicle.
文摘航空激光测距技术的发展推动了森林资源调查的技术革新。利用机载激光雷达(Light Detection and Ranging,LiDAR)数据能够精确测量森林结构。结合地面调查样本,LiDAR数据可在大范围内实现高分辨率的森林资源评估。文章以东北地区中8个样地作为研究对象,使用机载激光雷达点云数据实现对样地内单木林业信息的检核与更新。首先,基于剖面旋转算法,实现样地区域的单木分割。考虑到林业参数与树种的相关性,建立树种与分割树冠几何形态之间的对应关系,实现基于LiDAR数据的树种识别。在已知树种类别的基础上,提取样地内单木树高、冠幅、胸径、地上生物量和蓄积量等森林参数,实现林业参数的检核与更新。实验结果显示,树冠分割F 1分数超过95%,树种识别准确率超过90%,树高、东西冠幅、南北冠幅、胸径、地上生物量及蓄积量的决定系数R^(2)分别为89.3%、75.7%、69.4%、84.0%、89.6%和89.1%。结果表明:激光雷达调查方法实用性强且可以广泛应用于大范围林业精确调查中。
