LiDAR-based place recognition (LPR) plays a pivotal role in autonomous driving, which
assists Simultaneous Localization and Mapping (SLAM) systems in reducing accumulated …

Place recognition is a key module in robotic navigation. The existing line of studies mostly
focuses on visual place recognition to recognize previously visited places solely based on …

Visual place recognition has attracted widespread research interest in multiple fields such
as computer vision and robotics. Recently, researchers have employed advanced deep …

Where am I? This is one of the most critical questions that any intelligent system should
answer to decide whether it navigates to a previously visited area. This problem has long …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

Loop closure detection is an essential and challenging problem in simultaneous localization
and mapping (SLAM). It is often tackled with light detection and ranging (LiDAR) sensor due …

Autonomous Vehicles (AV) are becoming more capable of navigating in complex
environments with dynamic and changing conditions. A key component that enables these …

Global registration of multiview robot data is a challenging task. Appearance-based global
localization approaches often fail under drastic view-point changes, as representations have …

Place recognition is an important branch of Simultaneous Localization and Mapping
(SLAM), which finds revisited places, thereby reducing error accumulations. Most …

Place recognition is a challenging problem in mobile robotics, especially in unstructured
environments or under viewpoint and illumination changes. Most LiDAR-based methods rely …