This paper proposes the application of informed machine learning technique to enhance the
performance of an autonomous indoor navigation system by leveraging prior knowledge …

Visual simultaneous localization and mapping (VSLAM) is a foundational technology that
enables robots to achieve fully autonomous locomotion, exploration, inspection, and more …

Simultaneous localisation and mapping (SLAM) is the problem of autonomous robots to
construct or update a map of an undetermined unstructured environment while …

As autonomous driving technology continues to advance and gradually become a reality,
ensuring the safety of autonomous driving in complex traffic scenarios has become a key …

This work focuses on finding the extrinsic parameters (rotation and translation) between
Lidar and an RGB camera sensor. We use a planar checkerboard and place it inside the …

Lidar-assisted visual odometry is a widely used method for pose estimation. However,
existing lidar-visual odometry methods suffer from depth association errors, and single-point …

Indoor positioning technology is essential for indoor mobile robots and drones. However,
there has never been a general-purpose technology or infrastructure that enables indoor …

Visual localization is a fundamental task that regresses the 6 Degree Of Freedom (6DoF)
poses with image features in order to serve the high precision localization requests in many …

In the domain of mobile robot navigation, conventional path-planning algorithms typically
rely on predefined rules and prior map information, which exhibit significant limitations when …

基于激光同时定位与地图构建(simultaneous localization and mapping, SLAM) 技术,
不仅能够实现车辆在未知环境下的实时定位, 还能高效地获取环境的三维地理空间信息 …