An Indoor and Outdoor Navigation System for Visually Impaired People

In this paper, we present a system that allows visually impaired people to autonomously navigate in an unknown indoor and outdoor environment. The system, explicitly designed for low vision people, can be generalized to other users in an easy way. We assume that special landmarks are posed for helping the users in the localization of pre-defined paths. Our novel approach exploits the use of both the inertial sensors and the camera integrated into the smartphone as sensors. Such a navigation system can also provide direction estimates to the tracking system to the users. The success of out approach is proved both through experimental tests performed in controlled indoor environments and in real outdoor installations. A comparison with deep learning methods has been presented

Fluorescent particle tracers for surface hydrology

Surface water processes control downstream runoff phenomena, waste and pollutant diffusion, erosion mechanics, and sediment transport. However, current observational methodologies do not allow for the identification and kinematic characterization of the physical processes contributing to catchment dynamics. Traditional methodologies are not capable to cope with extreme in-situ conditions, including practical logistic challenges as well as inherent flow complexity. In addition, available observational techniques are non-exhaustive for describing multiscale hydrological processes. This research addresses the need for novel observations of the hydrological community by developing pioneer flow characterization approaches that rely on the mutual integration of traditional tracing techniques and state-of-the-art image-based sensing procedures. These novel methodologies enable the in-situ direct observation of surface water processes through remote and unsupervised procedures, thus paving the way to the development of distributed networks of sensing platforms for catchment-scale environmental sensing. More specifically, the proposed flow characterization methodology is a low-cost measurement system that can be applied to a variety of real-world settings spanning from few centimeters rills in natural catchments to riverine ecosystems. The technique is based on the use of in-house synthesized environmentally-friendly fluorescent particle tracers through digital cameras for direct flow measurement and travel time estimations. Automated image analysis-based procedures are developed for real-time flow characterization based on image manipulation, template-based correlation, particle image velocimetry, and dimensionality reduction methodologies. The feasibility of the approach is assessed through laboratory-designed experiments, where the accuracy of the methodology is investigated with respect to well-established flow visualization techniques. Further, the transition of the proposed flow characterization approach to natural settings is studied through paradigmatic observations of natural stream flows in small scale channel and riverine settings and overland flows in hillslope environments. The integration of the proposed flow sensing system in a stand-alone, remote, and mobile platform is explored through the design, development, and testing of a miniature aerial vehicle for environmental monitoring through video acquisition and processing

Taking Inspiration from Flying Insects to Navigate inside Buildings

These days, flying insects are seen as genuinely agile micro air vehicles fitted with smart sensors and also parsimonious in their use of brain resources. They are able to visually navigate in unpredictable and GPS-denied environments. Understanding how such tiny animals work would help engineers to figure out different issues relating to drone miniaturization and navigation inside buildings. To turn a drone of ~1 kg into a robot, miniaturized conventional avionics can be employed; however, this results in a loss of their flight autonomy. On the other hand, to turn a drone of a mass between ~1 g (or less) and ~500 g into a robot requires an innovative approach taking inspiration from flying insects both with regard to their flapping wing propulsion system and their sensory system based mainly on motion vision in order to avoid obstacles in three dimensions or to navigate on the basis of visual cues. This chapter will provide a snapshot of the current state of the art in the field of bioinspired optic flow sensors and optic flow-based direct feedback loops applied to micro air vehicles flying inside buildings

On-Orbit Results and Lessons Learned from the ASTERIA Space Telescope Mission

The Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) was deployed from the International Space Station (ISS) on 20 November 2017, beginning a technology demonstration and opportunistic science mission to advance the state of the art in nanosatellite performance for astrophysical observations. The goal of ASTERIA is to achieve arcsecond-level line-of-sight pointing error and highly stable focal plane temperature control. These capabilities enable precision photometry—i.e. the careful measurement of stellar brightness over time—which in turn allows investigation of astrophysical phenomena such as transiting exoplanets. By the end of the 90-day prime mission, ASTERIA had achieved line-of-sight pointing stability of approximately 0.5 arcseconds root mean square (RMS) over 20-minute observations, pointing repeatability of 1 milliarcsecond RMS from one observation to the next, and focal plane temperature stability better than ±0.01 K over 20-minute observations. This paper presents an overview of the ASTERIA flight and ground system, summarizes the pre-delivery test campaign, and discusses the on-orbit performance obtained by the pointing and thermal control subsystems. We also describe the process for planning opportunistic science observations and present lessons learned from development and operations. Having successfully operated for over 200 days as of this writing, ASTERIA is currently in an extended mission to observe nearby bright stars for transiting exoplanets

Vision-based methods for state estimation and control of robotic systems with application to mobile and surgical robots

For autonomous systems that need to perceive the surrounding environment for the accomplishment of a given task, vision is a highly informative exteroceptive sensory source. When gathering information from the available sensors, in fact, the richness of visual data allows to provide a complete description of the environment, collecting geometrical and semantic information (e.g., object pose, distances, shapes, colors, lights). The huge amount of collected data allows to consider both methods exploiting the totality of the data (dense approaches), or a reduced set obtained from feature extraction procedures (sparse approaches). This manuscript presents dense and sparse vision-based methods for control and sensing of robotic systems. First, a safe navigation scheme for mobile robots, moving in unknown environments populated by obstacles, is presented. For this task, dense visual information is used to perceive the environment (i.e., detect ground plane and obstacles) and, in combination with other sensory sources, provide an estimation of the robot motion with a linear observer. On the other hand, sparse visual data are extrapolated in terms of geometric primitives, in order to implement a visual servoing control scheme satisfying proper navigation behaviours. This controller relies on visual estimated information and is designed in order to guarantee safety during navigation. In addition, redundant structures are taken into account to re-arrange the internal configuration of the robot and reduce its encumbrance when the workspace is highly cluttered. Vision-based estimation methods are relevant also in other contexts. In the field of surgical robotics, having reliable data about unmeasurable quantities is of great importance and critical at the same time. In this manuscript, we present a Kalman-based observer to estimate the 3D pose of a suturing needle held by a surgical manipulator for robot-assisted suturing. The method exploits images acquired by the endoscope of the robot platform to extrapolate relevant geometrical information and get projected measurements of the tool pose. This method has also been validated with a novel simulator designed for the da Vinci robotic platform, with the purpose to ease interfacing and employment in ideal conditions for testing and validation. The Kalman-based observers mentioned above are classical passive estimators, whose system inputs used to produce the proper estimation are theoretically arbitrary. This does not provide any possibility to actively adapt input trajectories in order to optimize specific requirements on the performance of the estimation. For this purpose, active estimation paradigm is introduced and some related strategies are presented. More specifically, a novel active sensing algorithm employing visual dense information is described for a typical Structure-from-Motion (SfM) problem. The algorithm generates an optimal estimation of a scene observed by a moving camera, while minimizing the maximum uncertainty of the estimation. This approach can be applied to any robotic platforms and has been validated with a manipulator arm equipped with a monocular camera

Development of a multi-modal tactile force sensing system for deep-sea applications

With the increasing demand for autonomy in robotic systems, there is a rising need for sensory data sensed via different modalities. In this way system states and the aspects of unstructured environments can be assessed in the most detailed fashion possible, thus providing a basis for making decisions regarding the robotâ s task. Com- pared to other sensing modalities, the sense of touch is underrepresented in todayâ s robots. That is where this thesis comes in. A tactile sensing system is developed that combines several modalities of contact sensing. The use of the tactile sense in robotic grippers is of great relevance especially for robotic systems in the deep sea. Up to now manipulation systems in master-slave control mode have been used in this area of application. An operator performing the manipulation task has to rely on visual feedback coming from cameras. Working on the oceanâ s seafloor means having to cope with conditions of limited visibility caused by swirled-up sediment

Intelligent Agent Architectures: Reactive Planning Testbed

An Integrated Agent Architecture (IAA) is a framework or paradigm for constructing intelligent agents. Intelligent agents are collections of sensors, computers, and effectors that interact with their environments in real time in goal-directed ways. Because of the complexity involved in designing intelligent agents, it has been found useful to approach the construction of agents with some organizing principle, theory, or paradigm that gives shape to the agent's components and structures their relationships. Given the wide variety of approaches being taken in the field, the question naturally arises: Is there a way to compare and evaluate these approaches? The purpose of the present work is to develop common benchmark tasks and evaluation metrics to which intelligent agents, including complex robotic agents, constructed using various architectural approaches can be subjected

In-line quality control for Zero Defect Manufacturing: design, development and uncertainty analysis of vision-based instruments for dimensional measurements at different scales

Lo scopo di questo progetto di dottorato industriale finanziato attraverso una borsa di studio della Regione Marche è stato quello di sviluppare ricerca con potenziale impatto su un settore industriale, promuovere il coinvolgimento delle fabbriche e delle imprese locali nella ricerca e innovazione svolta in collaborazione con l'università e produrre ricerca in linea con le esigenze dell'ambiente industriale, non solo a livello regionale. Quindi, attraverso la collaborazione con una torneria locale (Zannini SpA) e una piccola azienda high-tech focalizzata sull'introduzione dell'innovazione meccatronica nel settore della tornitura (Z4Tec srl), e anche grazie a una collaborazione internazionale con l'Università di Anversa, abbiamo progettato e sviluppato nuovi strumenti per il controllo qualità in linea, basati su tecnologie senza contatto, in particolare tecnologie elettro-ottiche. Portando anche l'attenzione sull'importanza di prendere in considerazione l'incertezza, poiché è fondamentale nel processo decisionale basato sui dati che sono alla base di una strategia di Zero Defect Manufacturing. Infatti, la scarsa qualità delle misure può pregiudicare la qualità dei dati. In particolare, questo lavoro presenta due strumenti di misura che sono stati progettati e sviluppati con lo scopo di effettuare controllo qualità in linea di produzione e l’incertezza di misura di ogni strumento è stata analizzata in confronto ad altri strumenti presenti sul mercato. Nella parte finale di questo lavoro si è valutata l’incertezza di un profilometro a triangolazione di linea laser. Pertanto, la ricerca condotta in questa tesi può essere organizzata in due obiettivi principali: lo sviluppo di nuovi sistemi di misura dimensionale basati sulla visione da implementare in linea di produzione e l'analisi dell'incertezza di questi strumenti di misura. Per il primo obiettivo ci siamo concentrati su due tipi di misure dimensionali imposte dall'industria manifatturiera: macroscopiche (misure in mm) e microscopiche (misure in µm). Per le misure macroscopiche l'obiettivo era il controllo in linea della qualità dimensionale di pezzi torniti attraverso la profilometria ottica telecentrica. Il campione da ispezionare è stato posto tra l'illuminatore e l'obiettivo per ottenere la proiezione dell'ombra del campione. Le misure sono state eseguite mediante analisi grafica dell'immagine. Abbiamo discusso le disposizioni meccaniche mirate a ottimizzare le immagini acquisite e i problemi che eventuali disallineamenti meccanici dei componenti potrebbero introdurre nella qualità delle immagini. Per le misure microscopiche abbiamo progettato un sistema di misurazione della rugosità superficiale basato sulla visione retroilluminata, con l'obiettivo di determinare le condizioni ottimali di imaging utilizzando la modulation transfer function e l'uso di una electrically tunable lens. Un campione tornito (un cilindro) è posto di fronte a una telecamera ed è retroilluminato da una sorgente di luce collimata; tale configurazione ottica fornisce l'immagine del bordo del campione. Per testare la sensibilità del sistema di misura è stata utilizzata una serie di campioni di acciaio torniti con diverse rugosità superficiali. Per il secondo obiettivo, le tecniche di valutazione dell'incertezza di misura utilizzate in questo lavoro sono state un'analisi dell'incertezza statistica di tipo A e un'analisi Gage R&R. Nel caso del profilometro telecentrico, l'analisi è stata eseguita in confronto con altri dispositivi presenti sul mercato con un'analisi di tipo A e una Gage R&R. L'incertezza di misura del profilometro si è rivelata sufficiente per ottenere risultati nell'intervallo di tolleranza richiesto. Per il sistema di visione retroilluminato, il confronto dei risultati è stato effettuato con altri strumenti allo stato dell'arte, con un'analisi di Tipo A. Il confronto ha mostrato che le prestazioni dello strumento retroilluminato dipendono dai valori di rugosità superficiale considerati; mentre a valori maggiori di rugosità l'offset aumenta, per valori inferiori di rugosità i risultati sono compatibili con quelli dello strumento di riferimento (a stilo). Infine, sono state valutate la ripetibilità e la riproducibilità di un profilometro a triangolazione di linea laser, attraverso uno studio Gage R&R. Ogni punto di misura è stato ispezionato da tre operatori e l'insieme dei dati è stato elaborato con un'analisi dell'incertezza di Tipo A. Successivamente, uno studio Gage R&R ha contribuito a indagare la ripetibilità, la riproducibilità e la variabilità del sistema. Questa analisi ha dimostrato un'incertezza accettabile.The purpose of this industrial PhD project financed through a scholarship from the Regione Marche was to develop research with potential impact on an industrial sector, to promote the involvement of local factories and companies in research and innovation performed jointly with the university and to produce research in line with the needs of the industrial environment, not only at regional level. Hence, through collaborating with a local turning factory (Zannini SpA) and a small high-tech company focused on introducing mechatronic innovation in the turning sector (Z4Tec srl), and also thanks to an international collaboration with the University of Antwerp, we designed and developed new instruments for in-line quality control, based on non-contact technologies, specifically electro-optical technologies. While also bringing attention to the importance of taking uncertainty into consideration, since it is pivotal in data-based decision making which are at the base of a Zero Defect Manufacturing strategy. This means that poor quality of measurements can prejudice the quality of the data. In particular, this work presents two measurement instruments that were designed and developed for the purpose of in-line quality control and the uncertainty of each of the two instruments was evaluated and analyzed in comparison with instruments already present on the market. In the last part of this work, the uncertainty of a hand-held laser-line triangulation profilometer is estimated. Hence, the research conducted in this thesis can be organized in two main objectives: the development of new vision-based dimensional measurement systems to be implemented in production line and the uncertainty analysis of these measurement instruments. For the first objective we focused on two types of dimensional measurements imposed by the manufacturing industry: macroscopic (measuring dimensions in mm) and microscopic (measuring roughness in µm). For macroscopic measurements the target was the in-production dimensional quality control of turned parts through telecentric optical profilometry. The sample to be inspected was placed between illuminator and objective in order to obtain the projection of the shadow of the sample over a white background. Dimensional measurements were then performed by means of image processing over the image obtained. We discussed the mechanical arrangements targeted to optimize images acquired as well as the main issues that eventual mechanical misalignments of components might introduce in the quality of images. For microscopic measurements we designed a backlit vision-based surface roughness measurement system with a focus on smart behaviors such as determining the optimal imaging conditions using the modulation transfer function and the use of an electrically tunable lens. A turned sample (a cylinder) is placed in front of a camera and it is backlit by a collimated source of light; such optical configuration provides the image of the edge of the sample. A set of turned steel samples with different surface roughness was used to test the sensitivity of the measurement system. For the second objective, the measurement uncertainty evaluation techniques used in this work were a Type A statistical uncertainty analysis and a Gage R&R analysis. In the case of the telecentric profilometer, the analysis was performed in comparison with other on-the-market devices with a Type A analysis and a Gage R&R analysis. The measurement uncertainty of the profilometer proved to be sufficient to obtain results within the tolerance interval required. For the backlit vision system, the comparison of the results was made with other state-of-the-art instruments, with a Type A analysis. The comparison showed that the performance of the backlit instrument depends on the values of surface roughness considered; while at larger values of roughness the offset increases, the results are compatible with the ones of the reference instrument (stylus-based) at lower values of roughness. Lastly, the repeatability and reproducibility of a laser-line triangulation profilometer were assessed, through a Gage R&R study. Each measuring point was inspected by three different operators and the data set has been, at first, processed by a Type A uncertainty analysis. Then, a Gage R&R study helped investigate repeatability, reproducibility and the system variability. This analysis showed that the presented laser-line triangulation system has an acceptable uncertainty