With the rise of deep learning, there is a fundamental change in visual simultaneous
localization and mapping (SLAM) algorithms toward developing different modules trained as …

The low-texture, shape-similar, interconnected and mutual-occlusion nature of truss
members poses challenges for simultaneous localization and mapping of biped climbing …

Object SLAM uses additional semantic information to detect and map objects in the scene, in
order to improve the system's perception and map representation capabilities. Previous …

There are many possibilities for how to represent the map in simultaneous localisation and
mapping (SLAM). While sparse, keypoint-based SLAM systems have achieved impressive …

One of the challenges in autonomous robot navigation applications is recognizing the exact
location in a dynamic environment in which the location of surrounding objects changes …

This paper presents a novel framework to learn a concise geometric primitive representation
for 3D point clouds. Different from representing each type of primitive individually, we focus …

Existence of symmetric objects, whose observation at different viewpoints can be identical,
can deteriorate the performance of simultaneous localization and mapping (SLAM). This …

(东北大学信息科学与工程学院, 辽宁沈阳110819) 摘要: 视觉同时定位与地图构建(Visual
simultaneous localization and mapping, VSLAM) 是自主移动机器人, 自动驾驶, 增强现实(AR) …

Object-level SLAM introduces semantic meaningful and compact object landmarks that help
both indoor robot applications and outdoor autonomous driving tasks. However, the back …

For spatial perception, object-level SLAM (Simultaneous Localization and Mapping) has
shown an advantage by leveraging semantic information to comprehend unknown …