计算机应用研究2025，Vol.42Issue(1)：111-116,6.DOI:10.19734/j.issn.1001-3695.2024.06.0185
神经先验增强的抗干扰鲁棒自动驾驶导航
Neural prior based reconstruction for robust autonomous navigation against various disturbances
穆凡 1刘哲1
作者信息
- 1. 上海交通大学电子信息与电气工程学院,上海 200240
- 折叠
摘要
Abstract
Autonomous vehicles heavily rely on perception systems for urban navigation and environmental understanding.De-spite extensive researches about driving in favorable urban conditions,sensor failures and perception impairments under adverse weather and external interferences significantly impact the practical deployment of current autonomous driving systems.This paper proposed a neural prior-based autonomous driving information reconstruction algorithm for robust end-to-end naviga-tion.This algorithm densely stored scene geometry priors through implicit representation of driving scenarios and designed a reconstruction algorithm for perception based on the attention mechanism.In addition,it proposed a general framework to enhance the robustness of self-driving performance.Extensive experiments in the CARLA simulator demonstrate the generality and effectiveness of the proposed method,and the performance degradation rate of current self-driving models under external disturbances is reduced from 82.74％to 8.84％,which largely improves the driving performance of multiple existing self-driving models under external interferences.关键词
自动驾驶/鲁棒性/神经辐射场Key words
autonomous driving/robustness/neural radiance field分类
信息技术与安全科学引用本文复制引用
穆凡,刘哲..神经先验增强的抗干扰鲁棒自动驾驶导航[J].计算机应用研究,2025,42(1):111-116,6.
