Reina Giulio, Johnson David, Underwood James
Department of Engineering for Innovation, University of Salento, via Arnesano, 73100 Lecce, Italy.
Australian Centre for Field Robotics, University of Sydney, Rose Street Building (J04), 2006 Sydney, Australia.
Sensors (Basel). 2015 Jun 19;15(6):14661-78. doi: 10.3390/s150614661.
Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successfully in dusty, foggy, blizzard-blinding, and poorly lit scenarios. This paper presents a novel method for ground and obstacle segmentation based on radar sensing. The algorithm operates directly in the sensor frame, without the need for a separate synchronised navigation source, calibration parameters describing the location of the radar in the vehicle frame, or the geometric restrictions made in the previous main method in the field. Experimental results are presented in various urban scenarios to validate this approach, showing its potential applicability for advanced driving assistance systems and autonomous vehicle operations.
雷达克服了激光、立体视觉和声纳的缺点，因为它能够在尘土飞扬、雾气弥漫、暴雪致盲和光线昏暗的场景中成功运行。本文提出了一种基于雷达传感的地面和障碍物分割新方法。该算法直接在传感器框架中运行，无需单独的同步导航源、描述雷达在车辆框架中位置的校准参数，也无需该领域之前主要方法中的几何限制。在各种城市场景中给出了实验结果以验证该方法，展示了其在先进驾驶辅助系统和自动驾驶车辆操作中的潜在适用性。
