Conventional sensor-based localization relies on high-precision maps, which are generally
built using specialized map** techniques involving high labor and computational costs. In …

This work proposed a LiDAR-inertial-visual fusion framework termed R LIVE++ to achieve
robust and accurate state estimation while simultaneously reconstructing the radiance map …

Highly accurate and robust localization ability is of great importance for autonomous
vehicles (AVs) in urban scenarios. Traditional vision-based methods suffer from lost due to …

The environment of most real-world scenarios such as malls and supermarkets changes at
all times. A pre-built map that does not account for these changes becomes out-of-date …

Environment perception remains one of the key tasks in autonomous driving for which
solutions have yet to reach maturity. Multi-modal approaches benefit from the …

Large scale 3D maps constructed via LiDAR sensor are widely used on intelligent vehicles
for localization in outdoor scenes. However, loading, communication and processing of the …

In this paper, we compare different map management techniques for long-term visual
navigation in changing environments. In this scenario, the navigation system needs to …

Modern models that perform system-critical tasks such as segmentation and localization
exhibit good performance and robustness under ideal conditions (ie daytime, overcast) but …

摘要真实世界中存在光照, 天气, 季节及场景结构等复杂环境因素, 这些因素的改变对移动机器人
基本行为和任务能力带来巨大挑战. 随着机器人与人工智能技术的不断发展 …

6-DoF visual localization systems utilize principled approaches rooted in 3D geometry to
perform accurate camera pose estimation of images to a map. Current techniques use …