Sistema de localización indoor y outdoor para un mini vehículo aéreo autónomo no tripulado utilizando módulos wi-fi

Ante el constante desarrollo de la tecnología este ha dado origen a la demanda de aplicaciones, que precisan de más información del usuario, para la satisfacción de sus necesidades. La localización forma parte de tales necesidades, esto da lugar al avance de diferentes sistemas que reclaman precisión y rapidez en tiempo real, que sufren ciertas anomalías por el ruido, obstáculos, condiciones climáticas que provoca el sombreado, efecto multi-trayectoria y pérdida de la misma. El presente proyecto tiene como objetivo desarrollar un sistema de localización que considera el uso de módulos emisores y receptores que permiten mejorar el procesamiento y disminuir el consumo de energía, para optimar la estimación de posición en ambientes internos y externos en escenarios diferentes. Para llevar a cabo el diseño e implementación de este sistema sigue ciertas especificaciones de la metodología ciencia del diseño que da inicio a la construcción de nodos sensores inteligentes que modula y optimiza métodos de localización para el posicionamiento de un mini drone, que tiene como característica principal la navegación autónoma marcada por una ruta trazada. Se realizaron diferentes evaluaciones de estado (estático y dinámico) del UAV (Unmanned Aerial Vehicles, Vehículo Aéreo No Tripulado), en dos entornos diferentes cada uno con diferente magnitud, con los que se obtuvo el ángulo donde se encuentra la potencia máxima, y con ello el cálculo de error de precisión. Posteriormente se procede a interpretar cada uno de estos datos, determinando que el sistema de localización propuesto tiende a mejorar en cuanto a la estimación de localización y da opción a la modelación de un objeto o del ambiente en 3D o un medio fotográfico

Evaluation of DoS attacks on Commercial Wi-Fi-Based UAVs

One of the biggest challenges for the use of Unmanned Aerial Vehicles (UAVs) in large-scale real-world applications is security.  However, most of research projects related to robotics does not discuss security issues, moving on directly to studying classical problems (i.e., perception, control, planning). This paper evaluates the effects of availability issues (Denial of Service attacks) in two commonly used commercially available UAVs (AR.Drone 2.0 and 3DR SOLO). Denial of Service (DoS) attacks are made while the vehicles are navigating, simulating common conditions found both by the general public and in a research scenario. Experiments show how effective such attacks are and demonstrate actual security breaches that create specific vulnerabilities. The results indicate that both studied UAVs are susceptible to several types of DoS attacks which can critically influence the performance of UAVs during navigation, including a decrease in camera functionality, drops in telemetry feedback and lack of response to remote control commands. We also present a tool that can be used as a failsafe mechanism to alert the user when a drone is reaching out a determined flight limit range, avoiding availability issues

Scan matching by cross-correlation and differential evolution

Scan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable location-based services in autonomous mobile devices. Such devices usually have a wide range of high-resolution sensors but only a limited processing power and constrained energy supply. This work introduces a novel high-level scan matching strategy that uses a combination of two advanced algorithms recently used in this field: cross-correlation and differential evolution. The cross-correlation between two laser range scans is used as an efficient measure of scan alignment and the differential evolution algorithm is used to search for the parameters of a transformation that aligns the scans. The proposed method was experimentally validated and showed good ability to match laser range scans taken shortly after each other and an excellent ability to match laser range scans taken with longer time intervals between them.Web of Science88art. no. 85

Teleoperated visual inspection and surveillance with unmanned ground and aerial vehicles,” Int

Abstract—This paper introduces our robotic system named UGAV (Unmanned Ground-Air Vehicle) consisting of two semi-autonomous robot platforms, an Unmanned Ground Vehicle (UGV) and an Unmanned Aerial Vehicles (UAV). The paper focuses on three topics of the inspection with the combined UGV and UAV: (A) teleoperated control by means of cell or smart phones with a new concept of automatic configuration of the smart phone based on a RKI-XML description of the vehicles control capabilities, (B) the camera and vision system with the focus to real time feature extraction e.g. for the tracking of the UAV and (C) the architecture and hardware of the UAV

Collaboratively Navigating Autonomous Systems

The objective of this project is to focus on technologies for enabling heterogeneous networks of autonomous vehicles to cooperate together on a specific task. The prototyped test bed consists of a retrofitted electric golf cart and a quadrotor designed to perform distributed information gathering to guide decision making across the entire test bed. The system prototype demonstrates several aspects of this technology and lays the groundwork for future projects in this area

Unmanned Aerial Vehicle Black Box

This project created a stand-alone unit capable of providing on-board sensing and processing for robotic vehicles. This unit was designed to be compact, lightweight, inexpensive, and adaptable. The goal of this project is to help advance robotics research in mapping and multi-agent coordination by making it easier to equip vehicles to perform mapping and localization functions. Software integration for the sensing components was accomplished using the LSD-SLAM (Simultaneous Localization and Mapping) Package in ROS (Robot Operating System) and localization testing was done to verify functionality. Key Words: UAV, Robotics, Mapping, Localization, SLAM, Sensing, Processin

Accelerating Power Grid Monitoring with Flying Robots and Artificial Intelligence

The digital revolution is expected to surpass all previous economic transformations in scale, scope, and complexity. Digital technologies are making electrical grids more connected, more reliable, and sustainable. Several efforts have been made to revamp the electric grid and modernize century-old systems. In the near future, we expect to see a revolution in power grind monitoring with incredible results through artificial intelligence and big data, drones, among others. The business opportunity for using drones in the energy sector is impressive, although very few companies have joined in its implementation. The drone allows the safe remote overflight of high voltage power lines. They can be deployed to detect, inspect, and diagnose the defects of the power line infrastructure. In this article, we provide the state of the art of using drones in smart grid monitoring. We demonstrate and propose an architecture based on Faster R-CNN for detecting ice accretion on power lines. Finally, we shed light on opportunities and future trends of these emerging technologies that can guide future research directions

Multi-Robot Systems: Challenges, Trends and Applications

This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics

Open Aerial Map, Drones and Archaeology: The implications of using drones to contribute and share aerial data on an open data repository

The purpose of this research is to determine the potential benefits and challenges of volunteered aerial imagery by looking at OpenAerialMap (OAM) and by presenting how a repository like OAM may be applied in archaeological studies. The interviews and survey conducted in this research indicate that the main benefits of OAM are affordability, accessibility, rapid mapping and historic image preservation. Among the key challenges identified are concerns around data quality and privacy. Though most of the images on OAM are of high resolution, there is currently no way to guarantee the quality of images that people share on OAM. Similarly, there are no real safeguards against the misuse the openly available imagery. This is a prominent concern in archaeology, where open aerial images may increase the looting and destruction of heritage sites. Then again, OAM can aid in a number of ways in terms of archaeological research and it may even contribute to citizen engagement in archaeology. The research indicates that OAM is a positive endeavour that makes spatial data more accessible and provides drone users with the ability to engage in citizen science