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 …

In this letter, we introduce iBoW-LCD, a novel appearance-based loop-closure detection
method. The presented approach makes use of an incremental bag-of-words (BoW) scheme …

In the context of automated driving, navigating through challenging urban environments with
dynamic objects, large-scale scenes, and varying lighting/weather conditions, achieving …

Simultaneous localization and map** (SLAM) refers to a process that permits a mobile
robot to build up a map of the environment and, at the same time, to use it to compute its …

Due to its vast applicability, the semantic interpretation of regions or entities increasingly
attracts the attention of scholars within the robotics community. The paper at hand introduces …

Abstract Machine learning is constantly proving its capabilities by achieving exceptional
results in recognition and classification tasks. Image content recognition has been …

The modern view of things in the science of robotics imposes that when working in a human
environment, understanding of its equivalent semantics is required. In this paper, we present …

Loop-closure detection (LCD) has become an essential part of any simultaneous
localization and map** (SLAM) framework. It provides a means to rectify the drift error …

If we have been there before, we realize that viewing a single photograph is sufficient to
understand where the picture was captured. This fact highlights the impact of appearance …

The detection of pre-visited areas in robots' traversed path, widely known as loop closure
detection, is vital for drift and position correction in robotic applications, such as …