645 research outputs found
VSLAM and Navigation System of Unmanned Ground Vehicle Based on RGB-D Camera
In this thesis, ROS (Robot Operating System) is used as the software platform and a simple unmanned ground vehicle that is designed and constructed by myself is used as the hardware platform. The most critical issues in the navigation technology of unmanned ground vehicles in unknown environments -SLAM (Simultaneous Localization and Mapping) and autonomous navigation technology are studied. Through the analysis of the principle and structure of visual SLAM, a visual simultaneous localization and mapping algorithm is build. Moreover, accelerate the visual SLAM algorithm through hardware replacement and software algorithm optimization. RealSense D435 is used as the camera of the VSLAM sensor. The algorithm extracts the features from the data of depth camera and calculates the odometry information of the unmanned vehicle through the features matching of the adjacent image. Then update the vehicle’s location and map data using the odometry information.
Under the condition that the visual SLAM algorithm works normally, this thesis also uses the 3D map generated to derive the real-time 2D projection map. So as to apply it to the navigation algorithm. Then this thesis realize autonomous navigation and avoids the obstacle function of unmanned vehicle by controlling the driving speed and direction of the vehicle through the navigation algorithm using the 2D projection map. Unmanned ground vehicle path planning is mainly two parts: local path planning and global path planning. Global path planning is mainly used to plan the optimal path to the destination. Local path planning is mainly used to control the speed and direction of the UGV. This thesis analyzes and compares Dijkstra’s algorithm and A* algorithm. Considering the compatible to ROS, Dijkstra’s algorithm is finally used as the global path-planning algorithm. DWA (Dynamic Window Approach) algorithm is used as Local path planning. Under the control of the Dijkstra’s algorithm and the DWA algorithm, unmanned ground vehicles can automatically plan the optimal path to the target point and avoid obstacles. This thesis also designed and constructed a simple unmanned ground vehicle as an experimental platform and design a simple control method basing on differential wheeled unmanned ground vehicle and finally realized the autonomous navigation of unmanned ground vehicles and the function of avoiding obstacles through visual SLAM algorithm and autonomous navigation algorithm.
Finally, the main work and deficiencies of this thesis are summarized. And the prospects and difficulties of the research field of unmanned ground vehicles are presented
AnoML-IoT: An End to End Re-configurable Multi-protocol Anomaly Detection Pipeline for Internet of Things
The rapid development in ubiquitous computing has enabled the use of
microcontrollers as edge devices. These devices are used to develop truly
distributed IoT-based mechanisms where machine learning (ML) models are
utilized. However, integrating ML models to edge devices requires an
understanding of various software tools such as programming languages and
domain-specific knowledge. Anomaly detection is one of the domains where a high
level of expertise is required to achieve promising results. In this work, we
present AnoML which is an end-to-end data science pipeline that allows the
integration of multiple wireless communication protocols, anomaly detection
algorithms, deployment to the edge, fog, and cloud platforms with minimal user
interaction. We facilitate the development of IoT anomaly detection mechanisms
by reducing the barriers that are formed due to the heterogeneity of an IoT
environment. The proposed pipeline supports four main phases: (i) data
ingestion, (ii) model training, (iii) model deployment, (iv) inference and
maintaining. We evaluate the pipeline with two anomaly detection datasets while
comparing the efficiency of several machine learning algorithms within
different nodes. We also provide the source code
(https://gitlab.com/IOTGarage/anoml-iot-analytics) of the developed tools which
are the main components of the pipeline.Comment: Elsevier Internet of Things, Volume 16, 100437, December 202
Technologies for digital twin applications in construction
The construction industry is facing enormous pressure to adopt digital solutions to solve the industry's inherent problems. The digital twin has emerged as a solution that can update a BIM model with real-time data to achieve cyber-physical integration, enabling real-time monitoring of assets and activities and improving decision-making. The application of digital twins in the construction industry is still in its nascent stages but has been steadily growing over the past few years. A wide variety of emerging technologies are being used in the development of digital twins in diverse applications in construction but it is not immediately clear from the literature which ones are key to the successful development of digital twins, necessitating a systematic literature review with a focus on technologies. This paper aims to identify the key technologies used in the development of digital twins in construction in the existing literature, the research gaps and the potential areas for future research. This is achieved by conducting a systematic review of studies with demonstrative case studies and experimental setups in construction. Based on the observed research gaps, prominent future research directions are suggested, focusing on technologies in data transmission, interoperability and data integration and data processing and visualisation
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