Odometria visual monocular em robôs para a agricultura com camara(s) com lentes "olho de peixe"

One of the main challenges in robotics is to develop accurate localization methods that achieve acceptable runtime performances.One of the most common approaches is to use Global Navigation Satellite System such as GPS to localize robots.However, satellite signals are not full-time available in some kind of environments.The purpose of this dissertation is to develop a localization system for a ground robot.This robot is inserted in a project called RoMoVi and is intended to perform tasks like crop monitoring and harvesting in steep slope vineyards.This vineyards are localized in the Douro region which are characterized by the presence of high hills.Thus, the context of RoMoVi is not prosperous for the use of GPS-based localization systems.Therefore, the main goal of this work is to create a reliable localization system based on vision techniques and low cost sensors.To do so, a Visual Odometry system will be used.The concept of Visual Odometry is equivalent to wheel odometry but it has the advantage of not suffering from wheel slip which is present in these kind of environments due to the harsh terrain conditions.Here, motion is tracked computing the homogeneous transformation between camera frames, incrementally.However, this approach also presents some open issues.Most of the state of art methods, specially those who present a monocular camera system, don't perform good motion estimations in pure rotations.In some of them, motion even degenerates in these situations.Also, computing the motion scale is a difficult task that is widely investigated in this field.This work is intended to solve these issues.To do so, fisheye lens cameras will be used in order to achieve wide vision field of views

Pothole 3D Reconstruction With a Novel Imaging System and Structure From Motion Techniques

Machine vision based evaluation systems are receiving increased attention, day by day, for automated quality inspection of roads. Industrial pavement scanners consist of laser scanners and are very expensive, hence inaccessible for everyone. The proposed work presents a simple and novel approach for 3D reconstruction of potholes for an automated inspection and road surface evaluation. The technique utilizes a Structure from Motion based 3D reconstruction algorithm, along with laser triangulation, to generate 3D point clouds of potholes. Alongside, a novel low-cost system, consisting of a single camera and a laser pointer, is also proposed. Keypoint matching techniques are employed, with the 5-point algorithm, on successive image frames to generate a point cloud. However, this point cloud is not metric yet, without scale information. The scale ambiguity is solved by making use of the laser pointer, and using the principle of triangulation. The laser spot is also detected in the same image sequence that is used for point-cloud building, cutting down the image capturing and processing overhead. The system has been benchmarked on artificial indentations with known dimensions, proving the robustness of the measurement scheme and hardware. Static and dynamic tests have been performed. The mean depth errors for measurement made by the imager statically and at dynamic speeds of 10 km/hr, 15 km/hr, and 20 km/hr are 5.3%, 7.9%, 14.4%, and 26.6%, whereas for perimeter the errors are 5.2%, 6.83 %, 11.8%, and 27.8%. The proposed, low-cost technique shows promising results in generating 3D point clouds for potholes

MEMS Accelerometers

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc

On Martian Surface Exploration: Development of Automated 3D Reconstruction and Super-Resolution Restoration Techniques for Mars Orbital Images

Very high spatial resolution imaging and topographic (3D) data play an important role in modern Mars science research and engineering applications. This work describes a set of image processing and machine learning methods to produce the “best possible” high-resolution and high-quality 3D and imaging products from existing Mars orbital imaging datasets. The research work is described in nine chapters of which seven are based on separate published journal papers. These include a) a hybrid photogrammetric processing chain that combines the advantages of different stereo matching algorithms to compute stereo disparity with optimal completeness, fine-scale details, and minimised matching artefacts; b) image and 3D co-registration methods that correct a target image and/or 3D data to a reference image and/or 3D data to achieve robust cross-instrument multi-resolution 3D and image co-alignment; c) a deep learning network and processing chain to estimate pixel-scale surface topography from single-view imagery that outperforms traditional photogrammetric methods in terms of product quality and processing speed; d) a deep learning-based single-image super-resolution restoration (SRR) method to enhance the quality and effective resolution of Mars orbital imagery; e) a subpixel-scale 3D processing system using a combination of photogrammetric 3D reconstruction, SRR, and photoclinometric 3D refinement; and f) an optimised subpixel-scale 3D processing system using coupled deep learning based single-view SRR and deep learning based 3D estimation to derive the best possible (in terms of visual quality, effective resolution, and accuracy) 3D products out of present epoch Mars orbital images. The resultant 3D imaging products from the above listed new developments are qualitatively and quantitatively evaluated either in comparison with products from the official NASA planetary data system (PDS) and/or ESA planetary science archive (PSA) releases, and/or in comparison with products generated with different open-source systems. Examples of the scientific application of these novel 3D imaging products are discussed

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Design and Experimental Evaluation of a Hybrid Wheeled-Leg Exploration Rover in the Context of Multi-Robot Systems

With this dissertation, the electromechanic design, implementation, locomotion control, and experimental evaluation of a novel type of hybrid wheeled-leg exploration rover are presented. The actively articulated suspension system of the rover is the basis for advanced locomotive capabilities of a mobile exploration robot. The developed locomotion control system abstracts the complex kinematics of the suspension system and provides platform control inputs usable by autonomous behaviors or human remote control. Design and control of the suspension system as well as experimentation with the resulting rover are in the focus of this thesis. The rover is part of a heterogeneous modular multi-robot exploration system with an aspired sample return mission to the lunar south pole or currently hard-to-access regions on Mars. The multi-robot system pursues a modular and reconfigurable design methodology. It combines heterogeneous robots with different locomotion capabilities for enhanced overall performance. Consequently, the design of the multi-robot system is presented as the frame of the rover developments. The requirements for the rover design originating from the deployment in a modular multi-robot system are accentuated and summarized in this thesis

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Enhanced Monocular Visual Odometry Integrated with Laser Distance Meter for Astronaut Navigation

Visual odometry provides astronauts with accurate knowledge of their position and orientation. Wearable astronaut navigation systems should be simple and compact. Therefore, monocular vision methods are preferred over stereo vision systems, commonly used in mobile robots. However, the projective nature of monocular visual odometry causes a scale ambiguity problem. In this paper, we focus on the integration of a monocular camera with a laser distance meter to solve this problem. The most remarkable advantage of the system is its ability to recover a global trajectory for monocular image sequences by incorporating direct distance measurements. First, we propose a robust and easy-to-use extrinsic calibration method between camera and laser distance meter. Second, we present a navigation scheme that fuses distance measurements with monocular sequences to correct the scale drift. In particular, we explain in detail how to match the projection of the invisible laser pointer on other frames. Our proposed integration architecture is examined using a live dataset collected in a simulated lunar surface environment. The experimental results demonstrate the feasibility and effectiveness of the proposed method

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion