Social robots are required to work in daily life environments. The navigation algorithms they need to safely move through these environments require reliable sensor data. We present a novel approach to increase the ...

La arquitectura sostenible se ha convertido en un aspecto cada vez más relevante en la sociedad actual, y uno de sus principales pilares es la eficiencia energética en los edificios. En este sentido, la incorporación de ...

This paper presents a convolutional neural network (CNN) model for event detection from Unmanned Aerial Vehicles (UAV) in disaster environments. The model leverages the YOLOv5 network, specifically adapted for aerial images ...

Cloud robotics and the Internet of robotic things (IoRT) can boost the performance of human-robot cooperative teams in demanding environments (e.g., disaster response, mining, demolition, and nuclear sites) by allowing ...

This Project Summary paper reviews the main contributions and lessons learned from the TRUST-ROB project: “Towards Resilient UGV and UAV Manipulator Teams for Robotic Search and Rescue Tasks”, which has been developed ...

This paper evaluates four semantic segmentation models in Search-and-Rescue (SAR) scenarios obtained from ground vehicles. Two base models are used (U-Net and PSPNet) to compare different approaches to semantic segmentation, ...

- [The full description of the dataset can be found at: https://www.uma.es/robotics-and-mechatronics/info/124594/sar-datasets/ ] - Collection of multimodal raw data captured from a manned ...

Semantic segmentation has been successfully adopted for scenarios such as indoor, outdoor, urban scenes, and synthetic scenes, but applications with scarce labeled data such as search-and-rescue (SAR), have not been ...