Os Veículos Aéreos Não Tripulados (VANTs) são ideais para operações de risco e estressante para o ser humano são as chamadas dull, dirty and dangerous missions. Portanto, uma importante aplicação desse tipo de robô aéreo diz respeito a operações de busca envolvendo múltiplos VANTs cooperativos, em que há risco de colisões entre aeronaves e o tempo de um voo é limitado, entre outros fatores, pela capacidade de um piloto trabalhar sem descanso. Entretanto, apesar de atualmente verificar-se um crescente número de pesquisas envolvendo VANTs e do grande potencial existente na utilização de VANTs, operações de busca cooperativas ainda não estão ocorrendo. Esse assunto é uma área de estudo multidisciplinar e nascente, que possui diversas linhas de pesquisa. Diferentes algoritmos de navegação e padrões de busca foram estudados visando selecionar o(s) mais adequado(s). Além disso, apresenta-se, neste trabalho, uma visão geral sobre os mecanismos de coordenação multiagente e avalia a adequação de cada uma delas à coordenação distribuída de agentes (VANTs), visando cooperação. Assim, com o objetivo de melhorar o desempenho de uma operação de busca, esta pesquisa de mestrado propõe um modelo de VANTs cooperativos que combina mecanismos de coordenação multiagente, algoritmos de navegação e padrões de busca estabelecidos pelos principais órgãos responsáveis pelas operações de busca e salvamento. Visando avaliar a sensibilidade do percentual médio de detecção de objetos, bem como o tempo médio de busca, foi desenvolvido um simulador e milhares de simulações foram realizadas. Observou-se que, utilizando o modelo, VANTs cooperativos podem reduzir, em média, 57% do tempo de busca (comparando com uma busca de dois VANTs não cooperativos no mesmo cenário), mantendo a probabilidade média de detecção dos objetos próxima de 100% e sobrevoando apenas 30% do espaço de busca. / There are an increasing number of researches into UAV (Unmanned Aerial Vehicle) in the literature. These robots are quite suitable to dull, dirty and dangerous missions. Thus, an important application of these vehicles is the search operations involving multiple UAVs in which there is risk of collisions among aircrafts and the flight time is limited by the maximum time of pilot working hours. However, despite the huge potential use of the UAVs, cooperative search operations with this kind of flying robots are not yet occurring. This research topic is a new and multidisciplinary area of study in its beginning and there are several issues that can be studied, such as centralized versus decentralized control, path planning for cooperative flights, agent reasoning for UAV tactical planning, safety assessments, reliability in automatic target reconnaissance by cameras, agent coordination mechanisms applied to UAV cooperation and the application itself. Different path planning algorithms were studied aiming to attain the most suitable to these kinds of operations, and the conclusions are presented. In addition, official documents of Search and Rescue operations are also studied in order to know the best practices already established for this kind of operations, and, finally, an overview of the coordination multi-agent theory is presented and evaluated to achieve the UAV coordination. This work proposes a model that combines path planning algorithms, search patterns and multi-agent coordination techniques to obtain a cooperative UAV model. The great goal for cooperative UAV is to achieve such performance that the performance of the group overcomes the sum of the individual performances isolatedly. Then, aiming to analyze the average percentage of objects detection, and the average search time, a simulator was developed and thousands of simulations were run. It was observed that, using the proposed model, two cooperative UAVs can perform a search operation 57% faster than two non cooperative UAVs, keeping the average probability of objects detection approaching at 100% and flying only 30% of the search space.

O presente documento tem por objetivo apresentar a tese desenvolvida no programa de doutorado em Ciência da Computação e Matemática Computacional do ICMC/USP. Esta tese aborda o desenvolvimento de sistemas autônomos, de baixo custo, para supervisão de missão e segurança de voo em Veículos Aéreos Não Tripulados (VANTs). A supervisão da missão é assegurada através da implementação de um sistema do tipo Mission Oriented Sensor Array (MOSA), responsável pelo adequado cumprimento da missão. A segurança de voo é garantida pelo sistema In-Flight Awareness (IFA), que visa monitorar o funcionamento da aeronave. Os assuntos missão e segurança são complexos e os sistemas MOSA e IFA foram idealizados e desenvolvidos de forma independente, fundamentando-se na ideia de separação de interesses. O desenvolvimento desses sistemas foi baseado em dois modelos de referência: MOSA e IFA, propostos pela literatura. Em trabalhos anteriores da literatura, alguns sistemas do tipo MOSA e IFA foram propostos para situações específicas de missão. Numa outra abordagem, esta tese propõe um único sistema MOSA e IFA capaz de se adequar a um conjunto distinto de missões. Neste trabalho, foi desenvolvida toda arquitetura de comunicação que integra os sistemas MOSA e IFA. No entanto, apenas esses dois sistemas não são suficientes para fazer a execução da missão com segurança, necessitando-se de um sistema capaz de se comunicar com o Piloto Automático (AP) do VANT. Logo, um sistema capaz de enviar requisições e comandos ao AP foi também implementado. Através desses três sistemas, missões autônomas com desvio de obstáculos puderam ser realizadas sem intervenção humana, mesmo diante de situações críticas ao voo. Assegurar os aspectos de segurança e missão pode se tornar conflitante durante o voo, pois em situações emergenciais deve-se abortar a missão. Diferentes estratégias para planejamento e replanejamento de rotas, baseadas em computação evolutiva e heurísticas, foram desenvolvidas e integradas nos sistemas MOSA e IFA. Os sistemas, aqui propostos, foram validados em quatro etapas: (i) experimentos com o simulador de voo FlightGear; (ii) simulações com a técnica Software-In-The-Loop (SITL); (iii) simulações com a técnica Hardware-In- The-Loop (HITL); (iv) voos reais. Na última etapa, os sistemas foram embarcados em dois modelos de VANTs, desenvolvidos pelo grupo de pesquisa. Durante a experimentação, alguns modelos de pilotos automáticos (APM e Pixhawk), computadores de bordo (Raspberry Pi 3, Intel Edison e BeagleBone Black), planejadores de missão e replanejadores de rotas emergenciais foram avaliados. Ao todo, três planejadores de rotas e oito replanejadores são suportados pela plataforma autônoma. O sistema autônomo desenvolvido permite alterar missões com diferentes características de hardware e de software de forma fácil e transparente, sendo, desse modo, uma arquitetura com características plug and play. / This document aims to present the thesis developed in the doctoral program in Computer Science and Computational Mathematics at ICMC/USP. This thesis addresses the development of low- cost autonomous systems for mission supervision and flight safety in Unmanned Aerial Vehicles (UAVs). The mission supervision is ensured through the implementation of a Mission Oriented Sensor Array (MOSA) system, which is responsible for the proper fulfillment of the mission. The flight safety is guaranteed by the In-Flight Awareness (IFA) system, which aims to monitor the aircraft operation. The mission and safety issues are complex, and the MOSA and IFA systems were idealized and developed independently, based on the idea of separation of concerns. The development of these systems was based on two reference models: MOSA and IFA, proposed in the literature. In previous works of the literature, some MOSA and IFA systems have been proposed for specific mission situations. In another approach, this thesis proposes a single MOSA and IFA system capable of adapting to a distinct set of missions. All the communication architecture that integrates the MOSA and IFA systems were developed in this work. However, only these two systems are not sufficient to carry out the mission safely; a system that can communicate with the AutoPilot (AP) of the UAV its also needed. In this way, a system that is capable of sending commands and requests to the AP was implemented in this work. Through these three systems, autonomous missions with a diversion of obstacles could be carried out without human intervention, even in critical situations to the flight. Ensuring the safety and mission aspects can become conflicting during the flight because in hazards situations the mission must be aborted. Different strategies for path planning and path replanning, based on evolutionary computation and heuristics, were developed and integrated into the MOSA and IFA systems. The systems proposed here were validated in four stages: (i) experiments with FlightGear flight simulator; (ii) simulations using Software-In-The-Loop (SITL); (iii) simulations using Hardware- In-The-Loop (HITL); (iv) real flights. In the last stage, the systems were embedded in two models of UAVs, developed by the research group. During the experiment were evaluated some models of autopilots (APM and Pixhawk), companion computers (Raspberry Pi 3, Intel Edison and BeagleBone Black), mission planners and emergency route planners. In all, three route planners and eight replanners are supported by the autonomous platform. The developed autonomous system allows changing missions with different hardware and software characteristics in an easy and transparent way, being, therefore, an architecture with Plug and play characteristics.

North American civil infrastructures are aging. According to recent (2016) Canadian infrastructure report card, 33% of the Canadian municipal infrastructures are either in fair or below fair condition. The current deficit of replacing fair and poor municipal bridges (covers 26% of bridges) is 13 billion dollars. According to the latest report (2017) by American Society of Civil Engineers, the entire American infrastructure have been given a D+ condition rating. This includes some of the structural elements of infrastructures that pose a significant risk and there is an urgent need for frequent and effective inspection to ensure the safety of people. Visual inspection is a commonly used technique to detect and identify surface defects in bridge structures as it has been considered the most feasible method for decades. However, this currently used methodology is inadequate and unreliable as it is highly dependent on subjective human judgment. This labor-intensive approach for inspection requires huge investment in terms of an arrangement of temporary scaffoldings/permanent platforms, ladders, snooper trucks, and sometimes helicopters. To address these issues associated with visual inspection, the completed research suggests three innovative methods; 1) Combined use of Fuzzy logic and Image Processing Algorithm to quantify surface defects, 2) Unmanned Aerial Vehicle (UAV)-assisted American Association of State Highway and Transportation Officials (AASHTO) guideline-based damage assessment technique, and 3) Patent-pending multi-device robotics-based sensor data acquisition system for mapping and assessing defects in civil structures. To detect and quantify subsurface defects such as voids and delamination using a UAV system, another patent-pending UAV-based acoustic method is developed. It is a novel inspection apparatus that comprises of an acoustic signal generator coupled to a UAV. The acoustic signal generator includes a hammer to produce an acoustic signal in a structure using a UAV. An outcome of this innovative research is the development of a model to refine multiple commercially available NDT techniques’ data to detect and quantify subsurface defects. To achieve this, a total of nine 1800 mm × 460 mm reinforced concrete slabs with varying thicknesses of 100 mm, 150 mm and 200 mm are prepared. These slabs are designed to have artificially simulated defects like voids, debonding, honeycombing, and corrosion. To determine the performance of five NDT techniques, more than 300 data points are considered for each test. The experimental research shows that utilizing multiple techniques on a single structure to evaluate the defects, significantly lowers error and increases accuracy compared to that from a standalone test. To visualize the NDT data, two-dimensional NDT data maps are developed. This work presents an innovative method to interpret NDT data correctly as it compares the individual data points of slabs with no defects to slabs with simulated damage. For the refinement of NDT data, significance factor and logical sequential determination factor are proposed. / Graduate / 2020-09-06

Instrumented umanned aerial vehicles represent a new way of measuring turbulence in the atmospheric boundary layer. However, autonomous measurements require control methods with disturbance-rejection and altitude command-following capabilities. Filtered dynamic inversion is a control method with desirable disturbance-rejection and command-following properties, and this controller requires limited model information. We implement filtered dynamic inversion as the pitch controller in an altitude-hold autopilot. We design and numerically simulate the continuous-time and discrete-time filtered-dynamic-inversion controllers with anti-windup on a nonlinear aircraft model. Finally, we present results from a flight experiment comparing the filtered-dynamic-inversion controller to a classical proportional-integral controller. The experimental results show that the filtered-dynamic-inversion controller performs better than a proportional-integral controller at certain values of the parameter.

This dissertation describes the development of a requirements analysis methodology that takes into account the concept of operations and the hierarchical decomposition of aerospace systems. At the core of the methodology, the Analytic Network Process (ANP) is used to ensure the traceability between the qualitative and quantitative information present in the hierarchical model. The proposed methodology is implemented to the requirements definition of a hurricane tracker Unmanned Aerial Vehicle. Three research objectives are identified in this work; (1) improve the requirements mapping process by matching the stakeholder expectations with the concept of operations, systems and available resources; (2) reduce the epistemic uncertainty surrounding the requirements and requirements mapping; and (3) improve the requirements down-selection process by taking into account the level of importance of the criteria and the available resources. Several challenges are associated with the identification and definition of requirements. The complexity of the system implies that a large number of requirements are needed to define the systems. These requirements are defined early in the conceptual design, where the level of knowledge is relatively low and the level of uncertainty is large. The proposed methodology intends to increase the level of knowledge and reduce the level of uncertainty by guiding the design team through a structured process. To address these challenges, a new methodology is created to flow-down the requirements from the stakeholder expectations to the systems alternatives. A taxonomy of requirements is created to classify the information gathered during the problem definition. Subsequently, the operational and systems functions and measures of effectiveness are integrated to a hierarchical model to allow the traceability of the information. Monte Carlo methods are used to evaluate the variations of the hierarchical model elements and consequently reduce the epistemic uncertainty. The proposed methodology is applied to the design of a hurricane tracker Unmanned Aerial Vehicles to demonstrate the origin and impact of requirements on the concept of operations and systems alternatives. This research demonstrates that the hierarchical modeling methodology provides a traceable flow-down of the requirements from the problem definition to the systems alternatives phases of conceptual design.

This research work provides the development of an Adaptive Flight Control System (AFCS) for autonomous hover of a Rotary-wing Unmanned Aerial Vehicle (RUAV). Due to the complex, nonlinear and time-varying dynamics of the RUAV, indirect adaptive control using the Model Predictive Control (MPC) is utilised. The performance of the MPC mainly depends on the model of the RUAV used for predicting the future behaviour. Due to the complexities associated with the RUAV dynamics, a neural network based black box identification technique is used for modelling the behaviour of the RUAV. Auto-regressive neural network architecture is developed for offline and online modelling purposes. A hybrid modelling technique that exploits the advantages of both the offline and the online models is proposed. In the hybrid modelling technique, the predictions from the offline trained model are corrected by using the error predictions from the online model at every sample time. To reduce the computational time for training the neural networks, a principal component analysis based algorithm that reduces the dimension of the input training data is also proposed. This approach is shown to reduce the computational time significantly. These identification techniques are validated in numerical simulations before flight testing in the Eagle and RMAX helicopter platforms. Using the successfully validated models of the RUAVs, Neural Network based Model Predictive Controller (NN-MPC) is developed taking into account the non-linearity of the RUAVs and constraints into consideration. The parameters of the MPC are chosen to satisfy the performance requirements imposed on the flight controller. The optimisation problem is solved numerically using nonlinear optimisation techniques. The performance of the controller is extensively validated using numerical simulation models before flight testing. The effects of actuator and sensor delays and noises along with the wind gusts are taken into account during these numerical simulations. In addition, the robustness of the controller is validated numerically for possible parameter variations. The numerical simulation results are compared with a base-line PID controller. Finally, the NN-MPCs are flight tested for height control and autonomous hover. For these, SISO as well as multiple SISO controllers are used. The flight tests are conducted in varying weather conditions to validate the utility of the control technique. The NN-MPC in conjunction with the proposed hybrid modelling technique is shown to handle additional disturbances successfully. Extensive flight test results provide justification for the use of the NN-MPC technique as a reliable technique for control of non-linear complex dynamic systems such as RUAVs.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2011. / This thesis describes the design and implementation of a video compression development board as a standalone embedded system. The board can capture images, encode them and stream out a video to a destination over a wireless link. This project was done to allow users to test and develop video compression encoders that are designed for UAV applications. The board was designed to use an ADSP-BF533 Blackfin DSP from Analog Devices with the purpose of encoding images, which were captured by a camera module and then streamed out a video through a WiFi module. Moreover, an FPGA that has an interface to a logic analyzer, the DSP, the camera and the WiFi module, was added to accommodate other future uses, and to allow for the debugging of the board. The board was tested by loading a H.264 BP/MP encoder from Analog Devices to the DSP, where the DSP was integrated with the camera and the WiFi module. The test was successful and the board was able to encode a 2 MegaPixel picture at about 2 frames per second with a data rate of 186 Kbps. However, as the frame rate was only 2 frames per second, the video was somewhat jerky. It was found that the encoding time is a system limitation and that it has to be improved in order to increase the frame rate. A proposed solution involves dividing the captured picture into smaller segments and encoding each segment in parallel. Thereafter, the segments can be packed and streamed out. Further performance issues about the proposed structure are presented in the thesis.

Made available in DSpace on 2016-08-31T13:33:46Z (GMT). No. of bitstreams: 1 MoniqueFS_Dissert.pdf: 2578055 bytes, checksum: 595fd4f8c3d8d5457fa6c6eb6df6adff (MD5) Previous issue date: 2015-08-27 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / The Unmanned Aerial Vehicles (UAVs) have received increasing attention in recent years as a way to replace the expensive manned vehicles. At first, UAVs were used for military applications, and currently they are used in the research and development area, where control techniques for stability and airworthiness are the main objects of study. The full development of autonomous flight in all environments is still a challenge. In this regard, the general objective of this work is to control the propulsion system of a quadrotor UAV for indoor altitude control application. The quadrotor system developed in this work consists of frame, four propellers, flight controller, sensors, four brushless direct current motors (BLDC), electronic speed controller (ESC), battery, radio control transmitter, receiver and universal circuit battery eliminator (UBEC). The software used for the simulation of Proportional Integral Derivative (PID) control for motor speed and altitude control was Simulink®/MATLAB. For the control development, it was necessary to model the quadrotor system to obtain a mathematical representation that allows an analytical study consistent with the system behavior in practice. The mathematical modeling of the quadrotor was performed using the Euler-Lagrange formalism, because it has the same form in any system of generalized coordinates and it is more suitable for generalizations. Tests were done to ensure proper operation of each part of the system, and quadrotor experiments were performed to calculate the motor thrust factor and to identificate parameters of BLDC motors. From the parameters identified in the experiments, the transfer functions required in PID control simulation of BLDC motor speed and quadrotor altitude were obtained. The experiment relating to PID control of motor speed was performed and the obtained values were compared with the simulated ones. The simulations and tests showed expected responses compared to the results of studies reported in the literature. This work begins new researches on UAVs area at the Universidade Federal Rural do Semi-Árido (UFERSA) / Os Veículos Aéreos Não Tripulados (VANTs) têm recebido uma crescente atenção nos últimos anos como uma forma de substituir os veículos tripulados de alto custo. Inicialmente, os VANTs eram usados para aplicações militares e, atualmente são utilizados na área de pesquisa e desenvolvimento, onde as técnicas de controle para a estabilidade e navegabilidade de voos são os principais objetos de estudo. O desenvolvimento completo de voo autônomo em todos os ambientes ainda é um desafio. Neste sentido, o objetivo geral do trabalho é controlar o sistema de propulsão de um VANT do tipo quadricóptero para aplicação no controle de altitude do mesmo em ambientes fechados. O sistema do quadricóptero desenvolvido neste trabalho é composto por frame, quatro hélices, controlador de voo, sensores, quatro motores de corrente contínua sem escovas (BLDC), controlador de velocidade eletrônico (ESC), bateria, transmissor rádio-controlado, receptor e circuito universal eliminador de bateria (UBEC). O software utilizado para simulação do controle Proporcional Integral Derivativo (PID) de velocidade dos motores e do controle de altitude foi o Simulink®/MATLAB. Para o desenvolvimento do controle foi necessário modelar o sistema do quadricóptero para obter uma representação matemática que permita um estudo analítico coerente com o comportamento do sistema na prática. A modelagem matemática do quadricóptero foi realizada através do formalismo de Euler-Lagrange, por possuir a mesma forma em qualquer sistema de coordenadas generalizadas e ser mais adequado a generalizações. Testes foram feitos a fim de garantir o funcionamento adequado de cada parte do sistema do quadricóptero e experimentos foram realizados para o cálculo do fator de empuxo dos motores e para a identificação de parâmetros dos motores BLDC. A partir dos parâmetros identificados nos experimentos, foram obtidas as funções de transferência necessárias para serem utilizadas nas simulações de controle PID de velocidade do motor BLDC e de altitude do quadricóptero. Foi realizado o experimento referente ao controle PID de velocidade do motor e os valores obtidos foram comparados com os da simulação. As simulações e testes apresentaram respostas esperadas, comparados com os resultados de trabalhos relacionados na literatura. Este trabalho dá início a novas pesquisas na área de VANTs na Universidade Federal Rural do Semi-Árido (UFERSA)

A utilização de Veículos Aéreos Não Tripulados (VANTs), também chamados UAV (Unmanned Aerial Vehicle) vem ganhando espaço nas mais diversas áreas, tais como inspeções em linhas de transmissão e em torres de fracionamento de refinarias, entre outros. Já na construção civil, estudos recentes estão sendo focados na utilização dos VANTs para inspeção de pontes, viadutos e estradas. O presente trabalho visa fornecer uma análise para o uso de VANT na área civil, na detecção de manifestações patológicas em revestimentos de argamassa, de forma a auxiliar na procura por fissuras em fachadas, sobretudo aqueles que a visualização esteja prejudicada, seja pela distância ou pela acessibilidade difícil ao local. Este trabalho analisa possíveis implementações de dois algoritmos de processamentos de imagens desenvolvidos a partir da ferramenta MATLAB para a indicação de presença de fissuras na alvenaria, obtendo o desempenho destes diferentes algoritmos quando executados em software em plataforma que possibilite a embarcação em VANTs. Utilizando a geração automática de código em C a partir do ambiente MATLAB, é realizada uma análise temporal em plataforma ARM e RISC dos algoritmos propostos, demonstrando a oportunidade de utilização de dispositivos na tarefa de processamento de imagem para a aplicação proposta. Esta análise possibilita a previsão do comportamento na utilização de um VANT, uma vez que isto pode impactar na velocidade durante a aplicação e consequentemente sua autonomia. / The use of Unmanned Aerial Vehicles (UAVs), has been gaining space in several areas, such as inspections of transmission lines, refineries fractionation towers among others. In the construction, recent studies have been focused on the use of UAVs for inspection of bridges, viaducts and roads. The present study aims to provide an analysis using UAVs in the civil construction area, in the detection of pathologic manifestations mortar coatings in order to aid in the search for cracks in the facades especially those that visualization is impaired, or may be the distance the accessibility difficult to spot. This paper provides an analysis of two algorithms of image processing developed from the Matlab tool for indicating the presence of cracks in masonry, getting the performance of these different algorithms when implemented in software platform that enables the vessel in UAV. Using the automatic generation of C/C++ code from the MATLAB environment is performed the temporal analysis on ARM and RISC plataform of the proposed algorithms demonstrates the opportunity to use devices in the image processing task for the proposed application. This analysis allows the prediction of the behavior of a UAV using one since it can impact velocity during application, and therefore their autonomy.

Detecção de linhas de alta tensão em ambientes complexos é uma das tarefas mais desafiadoras em inspeções que utilizam Veículos Aéreos Não Tripulados (VANTs). Este trabalho foca em dar uma solução para este desafio, através do desenvolvimento de um algoritmo de controle de voo de precisão, que guie o VANT de maneira autônoma sobre as linhas de alta tensão. O algoritmo proposto é baseado em quatro etapas: Captura da Imagem, Filtragem da Imagem, Detecção das Linhas e Controle de Voo. Inicialmente a imagem é redimensionada para um tamanho em que as linhas fiquem em maior evidência, depois uma sequência de filtros é aplicada na imagem para reduzir ruído e evidenciar ainda mais as linhas. Depois deste pré-tratamento, um filtro de duas dimensões com formato similar ao de uma linha de alta tensão é usado para extrair os pixels pertencentes as bordas destas linhas. Após a aplicação do filtro de duas dimensões, a Transformada de Hough é aplicada na imagem resultante para detectar os segmentos de reta. Por fim, todos os dados obtidos no processamento da imagem são utilizados para guiar o VANT de maneira autônoma pelas linhas de transmissão. O algoritmo proposto apresenta um eficiente sistema de detecção de linhas de alta tensão, para auxiliar o controle de voo autônomo de um VANT, apresentando resultados convincentes. / Power lines detection in complex environments is one of the most important and challenging tasks in Unmanned Aerial Vehicles (UAV)-based inspections. This work focuses on tackling this challenge by developing a control algorithm to support fine grain UAV control to autonomously guide the aerial platform over the power lines. The proposed algorithm is based on four stages: Image Capturing, Image Filtering, Line Detection and Flight Control. Firstly, the image is cropped to a size that fits all the power lines, then a sequence of filters is applied in the image to reduce noise and highlight these lines. After all the image's pretreatment, a 2D filter with similar shape of a power transmission line is used to extract pixels that belongs to the line's edges. Then, the Hough Transform method detects the line segments in the edges result image. Lastly all the obtained data is used to autonomously guide a UAV over the power transmission lines. The proposed algorithm presents an efficient power transmission lines detecting system to support the autonomous UAV guidance, which presents convincing results.