激光雷达
计算机科学
雷达
遥感
传感器融合
人工智能
计算机视觉
雷达工程细节
雷达跟踪器
机器人
雷达成像
机器人学
探地雷达
电信
地质学
作者
Jim Hollinger,Brett Kutscher,Ryan Close
摘要
The capability to detect partially obscured objects is of interest to many communities, including ground vehicle robotics. The ability to find partially obscured objects can aid in automated navigation and planning algorithms used by robots. Two sensors often used for this task are Lidar and Radar. Lidar and Radar systems provide complementary data about the environment. Both are active sensing modalities and provide direct range measurements. However, they operate in very different portions of the radio frequency spectrum. By exploiting properties associated with the different frequency spectra, the sensors are able to compensate for each other's shortcomings. This makes them excellent candidates for sensor processing and data fusion systems. The benefits associated with Lidar and Radar sensor fusion for a ground vehicle application, using economical variants of these sensors, are presented. Special consideration is given to detecting objects partially obscured by light to medium vegetation.
科研通智能强力驱动
Strongly Powered by AbleSci AI