This paper proposes an innovative hazard identification and risk assessment mapping
model for Urban Search and Rescue (USAR) environments, concentrating on a 3D mapping …

This paper presents a strategy to autonomously explore unknown indoor environments,
focusing on 3D mapping of the environment and performing grid level semantic labeling to …

Scene perception technology helps robots identify the target areas that people refer to so
that it contributes to human–robot interaction, semantic navigation and other related tasks …

This work presents a methodology to apply Bayesian networks classifiers (BNCs) to the
problem of semantic localization in robotics. This task consists of determining where the …

This work deals with the graph-based semantic segmentation of a robot's traversed
environment using the Louvain algorithm. In recent years, semantic segmentation has been …

The demand for digitizing manufacturing and controlling processes has been steadily
increasing in recent years. Digitization relies on different techniques and equipment, which …

In this work, an incremental clustering approach to obtain compact hierarchical models of an
environment is developed and evaluated. This process is performed using an …

Currently, many tasks can be carried out using mobile robots. These robots must be able to
estimate their position in the environment to plan their actions correctly. Omnidirectional …

The swift development of autonomous vehicles raises the necessity of semantically mapping
the environment by producing distinguishable representations to recognise similar areas. To …

The contemporary SLAM mapping systems assume a static environment and build a map
that is then used for mobile robot navigation disregarding the dynamic changes in this …