43,850 research outputs found

    Fast and Robust Detection of Fallen People from a Mobile Robot

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    This paper deals with the problem of detecting fallen people lying on the floor by means of a mobile robot equipped with a 3D depth sensor. In the proposed algorithm, inspired by semantic segmentation techniques, the 3D scene is over-segmented into small patches. Fallen people are then detected by means of two SVM classifiers: the first one labels each patch, while the second one captures the spatial relations between them. This novel approach showed to be robust and fast. Indeed, thanks to the use of small patches, fallen people in real cluttered scenes with objects side by side are correctly detected. Moreover, the algorithm can be executed on a mobile robot fitted with a standard laptop making it possible to exploit the 2D environmental map built by the robot and the multiple points of view obtained during the robot navigation. Additionally, this algorithm is robust to illumination changes since it does not rely on RGB data but on depth data. All the methods have been thoroughly validated on the IASLAB-RGBD Fallen Person Dataset, which is published online as a further contribution. It consists of several static and dynamic sequences with 15 different people and 2 different environments

    Performance of grassed swale as stormwater quantity control in lowland area

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    Grassed swale is a vegetated open channel designed to attenuate stormwater through infiltration and conveying runoff into nearby water bodies, thus reduces peak flows and minimizes the causes of flood. UTHM is a flood-prone area due to located in lowland area, has high groundwater level and low infiltration rates. The aim of this study is to assess the performance of grassed swale as a stormwater quantity control in UTHM. Flow depths and velocities of swales were measured according to Six-Tenths Depth Method shortly after a rainfall event. Flow discharges of swales (Qswale) were evaluated by Mean- Section Method to determine the variations of Manning’s roughness coefficients (ncalculate) that results between 0.075 – 0.122 due to tall grass and irregularity of channels. Based on the values of Qswale between sections of swales, the percentages of flow attenuation are up to 54%. As for the flow conveyance of swales, Qswale were determined by Manning’s equation that divided into Qcalculate, evaluated using ncalculate, and Qdesign, evaluated using roughness coefficient recommended by MSMA (ndesign), to compare with flow discharges of drainage areas (Qpeak), evaluated by Rational Method with 10-year ARI. Each site of study has shown Qdesign is greater than Qpeak up to 59%. However, Qcalculate is greater than Qpeak only at a certain site of study up to 14%. The values of Qdesign also greater than Qcalculate up to 52% where it shows that the roughness coefficients as considered in MSMA are providing a better performance of swale. This study also found that the characteristics of the studied swales are comparable to the design consideration by MSMA. Based on these findings, grassed swale has the potential in collecting, attenuating, and conveying stormwater, which suitable to be applied as one of the best management practices in preventing flash flood at UTHM campus

    Virtual Exploration of Underwater Archaeological Sites : Visualization and Interaction in Mixed Reality Environments

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    This paper describes the ongoing developments in Photogrammetry and Mixed Reality for the Venus European project (Virtual ExploratioN of Underwater Sites, http://www.venus-project.eu). The main goal of the project is to provide archaeologists and the general public with virtual and augmented reality tools for exploring and studying deep underwater archaeological sites out of reach of divers. These sites have to be reconstructed in terms of environment (seabed) and content (artifacts) by performing bathymetric and photogrammetric surveys on the real site and matching points between geolocalized pictures. The base idea behind using Mixed Reality techniques is to offer archaeologists and general public new insights on the reconstructed archaeological sites allowing archaeologists to study directly from within the virtual site and allowing the general public to immersively explore a realistic reconstruction of the sites. Both activities are based on the same VR engine but drastically differ in the way they present information. General public activities emphasize the visually and auditory realistic aspect of the reconstruction while archaeologists activities emphasize functional aspects focused on the cargo study rather than realism which leads to the development of two parallel VR demonstrators. This paper will focus on several key points developed for the reconstruction process as well as both VR demonstrators (archaeological and general public) issues. The ?rst developed key point concerns the densi?cation of seabed points obtained through photogrammetry in order to obtain high quality terrain reproduction. The second point concerns the development of the Virtual and Augmented Reality (VR/AR) demonstrators for archaeologists designed to exploit the results of the photogrammetric reconstruction. And the third point concerns the development of the VR demonstrator for general public aimed at creating awareness of both the artifacts that were found and of the process with which they were discovered by recreating the dive process from ship to seabed

    A Unified Framework for Mutual Improvement of SLAM and Semantic Segmentation

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    This paper presents a novel framework for simultaneously implementing localization and segmentation, which are two of the most important vision-based tasks for robotics. While the goals and techniques used for them were considered to be different previously, we show that by making use of the intermediate results of the two modules, their performance can be enhanced at the same time. Our framework is able to handle both the instantaneous motion and long-term changes of instances in localization with the help of the segmentation result, which also benefits from the refined 3D pose information. We conduct experiments on various datasets, and prove that our framework works effectively on improving the precision and robustness of the two tasks and outperforms existing localization and segmentation algorithms.Comment: 7 pages, 5 figures.This work has been accepted by ICRA 2019. The demo video can be found at https://youtu.be/Bkt53dAehj

    An assisted navigation method for telepresence robots

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    Telepresence robots have emerged as a new means of interaction in remote environments. However, the use of such robots is still limited due to safety and usability issues when operating in human-like environments. This work addresses these issues by enhancing the robot navigation through a collaborative control method that assists the user to negotiate obstacles. The method has been implemented in a commercial telepresence robot and a user study has been conducted in order to test the suitability of our approach.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
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