At present, the rapid development of the new energy vehicle industry has also promoted the intelligence of automobiles. Meanwhile, multi-sensor fusion technology has become the core support for intelligent vehicles. By integrating data from various sensors such as lidar, millimeter-wave radar, cameras, and ultrasonic radar, the shortcomings of a single sensor can be effectively compensated for, thereby enhancing the accuracy, reliability, and robustness of environmental perception. This article explores the application of multi-sensor fusion technology in intelligent vehicles, with a focus on elaborating its crucial roles in environmental perception, target recognition, and path planning. By integrating the data from lidar, radar, cameras and ultrasonic sensors, the limitations of a single sensor have been effectively overcome, and a more stable and accurate perception system has been constructed. The article systematically reviews the current technical implementation schemes, the technical challenges faced (such as synchronous optimization and algorithm improvement), and looks forward to the future trends that support the development of autonomous driving systems.
Peng Wang (Thu,) studied this question.