Multimodal Object Detection and Ranging Based on Camera and Lidar Sensor Fusion for Autonomous Driving

Engineering notes

Key topics: autonomous driving, object detection, lidar, point cloud, sensor fusion, perception. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

A robust perception system is critical in autonomous driving. It is responsible for object detection, classification, and ranging under challenging circumstances. Camera and lidar sensors provide complementary information, and by combining these two modalities, we can increase the robustness and accuracy of the overall perception system. This paper presents the implementation of sensor fusion based perception using camera images and lidar point clouds for object detection and ranging in a real-time driving environment. The experiment results obtained with our test vehicle demonstrate that the perception of vehicle surroundings can be more effectively achieved by means of camera-lidar sensor fusion compared with using a single type of sensor.

Links and sources

• Official / arXiv page

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