80 research outputs found

    Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

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    Cilj ovog istraživanja je procena različitih low-cost senzora za merenje visine leta bespilotne letelice sa više rotora na malim visinama. Primenjene su metode filtriranja podataka i druge metode u cilju optimizacije performansi i tačnosti merenja senzora. Izvšrena su merenja visine leta, a podaci su uskladišteni za kasniju analizu u odnosu na stvarnu visinu leta. Izračunati su stepeni korelacije i srednja kvadratna greška u merenju senzora sa ciljem procene rada senzora. Na osnovu rezultata istraživanja moguće je odrediti izbor adekvatnog senzora za ovu specifičnu primenu. Ovo istraživanje je pokazalo da je u uslovima ovog eksperimenta najbolje rezultate imao lidar senzor Garmin LIDAR-Lite V3HP i senzor Bosch Sensortech BME280 sa mogućnošću istovremenog merenja vlažnosti vazduha, atmosferskog pritiska i temperature.The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor

    Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

    Get PDF
    Cilj ovog istraživanja je procena različitih low-cost senzora za merenje visine leta bespilotne letelice sa više rotora na malim visinama. Primenjene su metode filtriranja podataka i druge metode u cilju optimizacije performansi i tačnosti merenja senzora. Izvšrena su merenja visine leta, a podaci su uskladišteni za kasniju analizu u odnosu na stvarnu visinu leta. Izračunati su stepeni korelacije i srednja kvadratna greška u merenju senzora sa ciljem procene rada senzora. Na osnovu rezultata istraživanja moguće je odrediti izbor adekvatnog senzora za ovu specifičnu primenu. Ovo istraživanje je pokazalo da je u uslovima ovog eksperimenta najbolje rezultate imao lidar senzor Garmin LIDAR-Lite V3HP i senzor Bosch Sensortech BME280 sa mogućnošću istovremenog merenja vlažnosti vazduha, atmosferskog pritiska i temperature.The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor

    Laser Based Altimetry for Unmanned Aerial Vehicle Hovering Over a Snow Surface

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    A microwave radar for non-invasive snow stratigraphy measurements has been developed. Results were promising, but it failed to detect light powder snow in the air-snowpack interface. The aim of this thesis is to find and verify a system for estimating altitude on centimeter scale over a snow surface, independent of snow conditions. Also, relative pitch and roll angle estimation between the UAV and local surface should be resolved, to help directing the radar beam perpendicularly to the surface. After a variety of technical solutions were examined, we propose a system of three time-of-flight near-infrared altimeters pointing at different directions towards the surface. Experimental results showed RMS error of 1.39 cm for range estimation averaged over the most common snow types, and 2.81 cm for wet snow, which was the least reflective medium. An experiment conducted for an array of two altimeters scanning over a snow surface, showed that the local, relative surface tilt was found to be accurate within ±2° given that it was sufficiently planar. Further, the altitude RMS error was estimated to 1.57 cm. We conclude that the chosen altimeter was within the requirements, and that an array of three altimeters would give acceptable relative tilt estimation in to planes on the snow surface. The system should be subject to flight testing and implemented on UAV platform such that it can aid the microwave radar system during snow scanning

    Sensing Architecture for Terrestrial Crop Monitoring: Harvesting Data as an Asset

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    [EN] Very often, the root of problems found to produce food sustainably, as well as the origin of many environmental issues, derive from making decisions with unreliable or inexistent data. Datadriven agriculture has emerged as a way to palliate the lack of meaningful information when taking critical steps in the field. However, many decisive parameters still require manual measurements and proximity to the target, which results in the typical undersampling that impedes statistical significance and the application of AI techniques that rely on massive data. To invert this trend, and simultaneously combine crop proximity with massive sampling, a sensing architecture for automating crop scouting from ground vehicles is proposed. At present, there are no clear guidelines of how monitoring vehicles must be configured for optimally tracking crop parameters at high resolution. This paper structures the architecture for such vehicles in four subsystems, examines the most common components for each subsystem, and delves into their interactions for an efficient delivery of high-density field data from initial acquisition to final recommendation. Its main advantages rest on the real time generation of crop maps that blend the global positioning of canopy location, some of their agronomical traits, and the precise monitoring of the ambient conditions surrounding such canopies. As a use case, the envisioned architecture was embodied in an autonomous robot to automatically sort two harvesting zones of a commercial vineyard to produce two wines of dissimilar characteristics. The information contained in the maps delivered by the robot may help growers systematically apply differential harvesting, evidencing the suitability of the proposed architecture for massive monitoring and subsequent data-driven actuation. While many crop parameters still cannot be measured non-invasively, the availability of novel sensors is continually growing; to benefit from them, an efficient and trustable sensing architecture becomes indispensable.This research was funded by the European Union's Horizon 2020 research and innovation program with grant agreement number 737669 entitled VineScout: Intelligent decisions from vineyard robots.Rovira Más, F.; Saiz Rubio, V.; Cuenca-Cuenca, A. (2021). Sensing Architecture for Terrestrial Crop Monitoring: Harvesting Data as an Asset. Sensors. 21(9):1-24. https://doi.org/10.3390/s21093114S12421

    Machine Vision: Approaches and Limitations

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    Review of Ultrasonic Ranging Methods and Their Current Challenges

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    Ultrasonic ranging has been widely used in automobiles, unmanned aerial vehicles (UAVs), robots and other fields. With the appearance of micromachined ultrasonic transducers (MUTs), the application of ultrasonic ranging technology presents a more extensive trend. This review focuses on ultrasonic ranging technology and its development history and future trend. Going through the state-of-the-art ultrasonic ranging methods, this paper covers the principles of each method, the signal processing methodologies, the overall system performance as well as key ultrasonic transducer parameters. Moreover, the error sources and compensation methods of ultrasonic ranging systems are discussed. This review aims to give an overview of the ultrasonic ranging technology including its current development and challenges

    NASA Tech Briefs, January 1990

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    Topics include: Electronic Components and Circuits. Electronic Systems, Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Fabrication Technology, Mathematics and Information Sciences, and Life Science

    Ispitivanje vremenske sinhronizovanosti mernih signala snimljenih MEMS akcelerometrima

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    U radu je opisano ispitivanje sinhronizovanosti podataka koji su uzorkovani putem odvojenih MEMS akcelerometara. Korišćeni su bežični senzorski uređaji razvijeni na Građevinskom fakultetu u Beogradu, namenjeni merenju vibracija građevinskih objekata. Poznato je da ovi uređaji mogu da postignu tačnost vremenskog označavanja uzoraka reda veličine10 μs za kraće merne periode (ispodminuta). Ovo znači da je greška koju elektronika unosi zanemarljiva za merenje mehaničkih veličina sa frekvencijom uzorkovanja reda veličine kHz. Analizirane su varijacije u fazi izlaznih signala različitih senzora prilikom identične pobude. Problem je ograničena mogućnost ostvarivanja identične mehaničke pobude na različitim mestima u prostoru, te je bez savršene opreme nemoguće razgraničiti koliki deo greške potiče od nepoklapanja ulaznih signala, a koliki od nesavršenosti senzorskog aparata. Pokazano je da je moguće dobiti standardnu devijaciju vremenskog ofseta između snimljenih signala reda veličine milisekunde

    Bridge Inspection: Human Performance, Unmanned Aerial Systems and Automation

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    Unmanned aerial systems (UASs) have become of considerable private and commercial interest for a variety of jobs and entertainment in the past 10 years. This paper is a literature review of the state of practice for the United States bridge inspection programs and outlines how automated and unmanned bridge inspections can be made suitable for present and future needs. At its best, current technology limits UAS use to an assistive tool for the inspector to perform a bridge inspection faster, safer, and without traffic closure. The major challenges for UASs are satisfying restrictive Federal Aviation Administration regulations, control issues in a GPS-denied environment, pilot expenses and availability, time and cost allocated to tuning, maintenance, post-processing time, and acceptance of the collected data by bridge owners. Using UASs with self-navigation abilities and improving image-processing algorithms to provide results near real-time could revolutionize the bridge inspection industry by providing accurate, multi-use, autonomous three-dimensional models and damage identification

    Low computational SLAM for an autonomous indoor aerial inspection vehicle

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    The past decade has seen an increase in the capability of small scale Unmanned Aerial Vehicle (UAV) systems, made possible through technological advancements in battery, computing and sensor miniaturisation technology. This has opened a new and rapidly growing branch of robotic research and has sparked the imagination of industry leading to new UAV based services, from the inspection of power-lines to remote police surveillance. Miniaturisation of UAVs have also made them small enough to be practically flown indoors. For example, the inspection of elevated areas in hazardous or damaged structures where the use of conventional ground-based robots are unsuitable. Sellafield Ltd, a nuclear reprocessing facility in the U.K. has many buildings that require frequent safety inspections. UAV inspections eliminate the current risk to personnel of radiation exposure and other hazards in tall structures where scaffolding or hoists are required. This project focused on the development of a UAV for the novel application of semi-autonomously navigating and inspecting these structures without the need for personnel to enter the building. Development exposed a significant gap in knowledge concerning indoor localisation, specifically Simultaneous Localisation and Mapping (SLAM) for use on-board UAVs. To lower the on-board processing requirements of SLAM, other UAV research groups have employed techniques such as off-board processing, reduced dimensionality or prior knowledge of the structure, techniques not suitable to this application given the unknown nature of the structures and the risk of radio-shadows. In this thesis a novel localisation algorithm, which enables real-time and threedimensional SLAM running solely on-board a computationally constrained UAV in heavily cluttered and unknown environments is proposed. The algorithm, based on the Iterative Closest Point (ICP) method utilising approximate nearest neighbour searches and point-cloud decimation to reduce the processing requirements has successfully been tested in environments similar to that specified by Sellafield Ltd
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