On the Calibration of Active Binocular and RGBD Vision Systems for Dual-Arm Robots

This paper describes a camera and hand-eye calibration methodology for integrating an active binocular robot head within a dual-arm robot. For this purpose, we derive the forward kinematic model of our active robot head and describe our methodology for calibrating and integrating our robot head. This rigid calibration provides a closedform hand-to-eye solution. We then present an approach for updating dynamically camera external parameters for optimal 3D reconstruction that are the foundation for robotic tasks such as grasping and manipulating rigid and deformable objects. We show from experimental results that our robot head achieves an overall sub millimetre accuracy of less than 0.3 millimetres while recovering the 3D structure of a scene. In addition, we report a comparative study between current RGBD cameras and our active stereo head within two dual-arm robotic testbeds that demonstrates the accuracy and portability of our proposed methodology

Accurate and Interactive Visual-Inertial Sensor Calibration with Next-Best-View and Next-Best-Trajectory Suggestion

Visual-Inertial (VI) sensors are popular in robotics, self-driving vehicles, and augmented and virtual reality applications. In order to use them for any computer vision or state-estimation task, a good calibration is essential. However, collecting informative calibration data in order to render the calibration parameters observable is not trivial for a non-expert. In this work, we introduce a novel VI calibration pipeline that guides a non-expert with the use of a graphical user interface and information theory in collecting informative calibration data with Next-Best-View and Next-Best-Trajectory suggestions to calibrate the intrinsics, extrinsics, and temporal misalignment of a VI sensor. We show through experiments that our method is faster, more accurate, and more consistent than state-of-the-art alternatives. Specifically, we show how calibrations with our proposed method achieve higher accuracy estimation results when used by state-of-the-art VI Odometry as well as VI-SLAM approaches. The source code of our software can be found on: https://github.com/chutsu/yac.Comment: 8 pages, 11 figures, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023

Real-time spatial modeling to detect and track resources on construction sites

For more than 10 years the U.S. construction industry has experienced over 1,000 fatalities annually. Many fatalities may have been prevented had the individuals and equipment involved been more aware of and alert to the physical state of the environment around them. Awareness may be improved by automatic 3D (three-dimensional) sensing and modeling of the job site environment in real-time. Existing 3D modeling approaches based on range scanning techniques are capable of modeling static objects only, and thus cannot model in real-time dynamic objects in an environment comprised of moving humans, equipment, and materials. Emerging prototype 3D video range cameras offer another alternative by facilitating affordable, wide field of view, automated static and dynamic object detection and tracking at frame rates better than 1Hz (real-time). This dissertation presents an imperical work and methodology to rapidly create a spatial model of construction sites and in particular to detect, model, and track the position, dimension, direction, and velocity of static and moving project resources in real-time, based on range data obtained from a three-dimensional video range camera in a static or moving position. Existing construction site 3D modeling approaches based on optical range sensing technologies (laser scanners, rangefinders, etc.) and 3D modeling approaches (dense, sparse, etc.) that offered potential solutions for this research are reviewed. The choice of an emerging sensing tool and preliminary experiments with this prototype sensing technology are discussed. These findings led to the development of a range data processing algorithm based on three-dimensional occupancy grids which is demonstrated in detail. Testing and validation of the proposed algorithms have been conducted to quantify the performance of sensor and algorithm through extensive experimentation involving static and moving objects. Experiments in indoor laboratory and outdoor construction environments have been conducted with construction resources such as humans, equipment, materials, or structures to verify the accuracy of the occupancy grid modeling approach. Results show that modeling objects and measuring their position, dimension, direction, and speed had an accuracy level compatible to the requirements of active safety features for construction. Results demonstrate that video rate 3D data acquisition and analysis of construction environments can support effective detection, tracking, and convex hull modeling of objects. Exploiting rapidly generated three-dimensional models for improved visualization, communications, and process control has inherent value, broad application, and potential impact, e.g. as-built vs. as-planned comparison, condition assessment, maintenance, operations, and construction activities control. In combination with effective management practices, this sensing approach has the potential to assist equipment operators to avoid incidents that result in reduce human injury, death, or collateral damage on construction sites.Civil, Architectural, and Environmental Engineerin

Real Time Stereo Cameras System Calibration Tool and Attitude and Pose Computation with Low Cost Cameras

The Engineering in autonomous systems has many strands. The area in which this work falls, the artificial vision, has become one of great interest in multiple contexts and focuses on robotics. This work seeks to address and overcome some real difficulties encountered when developing technologies with artificial vision systems which are, the calibration process and pose computation of robots in real-time. Initially, it aims to perform real-time camera intrinsic (3.2.1) and extrinsic (3.3) stereo camera systems calibration needed to the main goal of this work, the real-time pose (position and orientation) computation of an active coloured target with stereo vision systems. Designed to be intuitive, easy-to-use and able to run under real-time applications, this work was developed for use either with low-cost and easy-to-acquire or more complex and high resolution stereo vision systems in order to compute all the parameters inherent to this same system such as the intrinsic values of each one of the cameras and the extrinsic matrices computation between both cameras. More oriented towards the underwater environments, which are very dynamic and computationally more complex due to its particularities such as light reflections. The available calibration information, whether generated by this tool or loaded configurations from other tools allows, in a simplistic way, to proceed to the calibration of an environment colorspace and the detection parameters of a specific target with active visual markers (4.1.1), useful within unstructured environments. With a calibrated system and environment, it is possible to detect and compute, in real time, the pose of a target of interest. The combination of position and orientation or attitude is referred as the pose of an object. For performance analysis and quality of the information obtained, this tools are compared with others already existent.A engenharia de sistemas autónomos actua em diversas vertentes. Uma delas, a visão artificial, em que este trabalho assenta, tornou-se uma das de maior interesse em múltiplos contextos e focos na robótica. Assim, este trabalho procura abordar e superar algumas dificuldades encontradas aquando do desenvolvimento de tecnologias baseadas na visão artificial. Inicialmente, propõe-se a fornecer ferramentas para realizar as calibrações necessárias de intrínsecos (3.2.1) e extrínsecos (3.3) de sistemas de visão stereo em tempo real para atingir o objectivo principal, uma ferramenta de cálculo da posição e orientação de um alvo activo e colorido através de sistemas de visão stereo. Desenhadas para serem intuitivas, fáceis de utilizar e capazes de operar em tempo real, estas ferramentas foram desenvolvidas tendo em vista a sua integração quer com camaras de baixo custo e aquisição fácil como com camaras mais complexas e de maior resolução. Propõem-se a realizar a calibração dos parâmetros inerentes ao sistema de visão stereo como os intrínsecos de cada uma das camaras e as matrizes de extrínsecos que relacionam ambas as camaras. Este trabalho foi orientado para utilização em meio subaquático onde se presenciam ambientes com elevada dinâmica visual e maior complexidade computacional devido `a suas particularidades como reflexões de luz e má visibilidade. Com a informação de calibração disponível, quer gerada pelas ferramentas fornecidas, quer obtida a partir de outras, pode ser carregada para proceder a uma calibração simplista do espaço de cor e dos parâmetros de deteção de um alvo específico com marcadores ativos coloridos (4.1.1). Estes marcadores são ´uteis em ambientes não estruturados. Para análise da performance e qualidade da informação obtida, as ferramentas de calibração e cálculo de pose (posição e orientação), serão comparadas com outras já existentes

3D Sensor Placement and Embedded Processing for People Detection in an Industrial Environment

Papers I, II and III are extracted from the dissertation and uploaded as separate documents to meet post-publication requirements for self-arciving of IEEE conference papers.At a time when autonomy is being introduced in more and more areas, computer vision plays a very important role. In an industrial environment, the ability to create a real-time virtual version of a volume of interest provides a broad range of possibilities, including safety-related systems such as vision based anti-collision and personnel tracking. In an offshore environment, where such systems are not common, the task is challenging due to rough weather and environmental conditions, but the result of introducing such safety systems could potentially be lifesaving, as personnel work close to heavy, huge, and often poorly instrumented moving machinery and equipment. This thesis presents research on important topics related to enabling computer vision systems in industrial and offshore environments, including a review of the most important technologies and methods. A prototype 3D sensor package is developed, consisting of different sensors and a powerful embedded computer. This, together with a novel, highly scalable point cloud compression and sensor fusion scheme allows to create a real-time 3D map of an industrial area. The question of where to place the sensor packages in an environment where occlusions are present is also investigated. The result is algorithms for automatic sensor placement optimisation, where the goal is to place sensors in such a way that maximises the volume of interest that is covered, with as few occluded zones as possible. The method also includes redundancy constraints where important sub-volumes can be defined to be viewed by more than one sensor. Lastly, a people detection scheme using a merged point cloud from six different sensor packages as input is developed. Using a combination of point cloud clustering, flattening and convolutional neural networks, the system successfully detects multiple people in an outdoor industrial environment, providing real-time 3D positions. The sensor packages and methods are tested and verified at the Industrial Robotics Lab at the University of Agder, and the people detection method is also tested in a relevant outdoor, industrial testing facility. The experiments and results are presented in the papers attached to this thesis.publishedVersio

View generated database

This document represents the final report for the View Generated Database (VGD) project, NAS7-1066. It documents the work done on the project up to the point at which all project work was terminated due to lack of project funds. The VGD was to provide the capability to accurately represent any real-world object or scene as a computer model. Such models include both an accurate spatial/geometric representation of surfaces of the object or scene, as well as any surface detail present on the object. Applications of such models are numerous, including acquisition and maintenance of work models for tele-autonomous systems, generation of accurate 3-D geometric/photometric models for various 3-D vision systems, and graphical models for realistic rendering of 3-D scenes via computer graphics

Large volume artefact for calibration of multi-sensor projected fringe systems

Fringe projection is a commonly used optical technique for measuring the shapes of objects with dimensions of up to about 1 m across. There are however many instances in the aerospace and automotive industries where it would be desirable to extend the benefits of the technique (e.g., high temporal and spatial sampling rates, non-contacting measurements) to much larger measurement volumes. This thesis describes a process that has been developed to allow the creation of a large global measurement volume from two or more independent shape measurement systems. A new 3-D large volume calibration artefact, together with a hexapod positioning stage, have been designed and manufactured to allow calibration of volumes of up to 3 x 1 x 1 m3. The artefact was built from carbon fibre composite tubes, chrome steel spheres, and mild steel end caps with rare earth rod magnets. The major advantage over other commonly used artefacts is the dimensionally stable relationship between features spanning multiple individual measurement volumes, thereby allowing calibration of several scanners within a global coordinate system, even when they have non-overlapping fields of view. The calibration artefact is modular, providing the scalability needed to address still larger measurement volumes and volumes of different geometries. Both it and the translation stage are easy to transport and to assemble on site. The artefact also provides traceabitity for calibration through independent measurements on a mechanical CMM. The dimensions of the assembled artefact have been found to be consistent with those of the individual tube lengths, demonstrating that gravitational distortion corrections are not needed for the artefact size considered here. Deformations due to thermal and hygral effects have also been experimentally quantified. The thesis describes the complete calibration procedure: large volume calibration artefact design, manufacture and testing; initial estimation of the sensor geometry parameters; processing of the calibration data from manually selected regions-of-interest (ROI) of the artefact features; artefact pose estimation; automated control point selection, and finally bundle adjustment. An accuracy of one part in 17 000 of the global measurement volume diagonal was achieved and verified