Reliability Testing Procedure for MEMS IMUs Applied to Vibrating Environments

The diffusion of micro electro-mechanical systems (MEMS) technology applied to navigation systems is rapidly increasing, but currently, there is a lack of knowledge about the reliability of this typology of devices, representing a serious limitation to their use in aerospace vehicles and other fields with medium and high requirements. In this paper, a reliability testing procedure for inertial sensors and inertial measurement units (IMU) based on MEMS for applications in vibrating environments is presented. The sensing performances were evaluated in terms of signal accuracy, systematic errors, and accidental errors; the actual working conditions were simulated by means of an accelerated dynamic excitation. A commercial MEMS-based IMU was analyzed to validate the proposed procedure. The main weaknesses of the system have been localized by providing important information about the relationship between the reliability levels of the system and individual components

Innovative Solutions for Navigation and Mission Management of Unmanned Aircraft Systems

The last decades have witnessed a significant increase in Unmanned Aircraft Systems (UAS) of all shapes and sizes. UAS are finding many new applications in supporting several human activities, offering solutions to many dirty, dull, and dangerous missions, carried out by military and civilian users. However, limited access to the airspace is the principal barrier to the realization of the full potential that can be derived from UAS capabilities. The aim of this thesis is to support the safe integration of UAS operations, taking into account both the user's requirements and flight regulations. The main technical and operational issues, considered among the principal inhibitors to the integration and wide-spread acceptance of UAS, are identified and two solutions for safe UAS operations are proposed: A. Improving navigation performance of UAS by exploiting low-cost sensors. To enhance the performance of the low-cost and light-weight integrated navigation system based on Global Navigation Satellite System (GNSS) and Micro Electro-Mechanical Systems (MEMS) inertial sensors, an efficient calibration method for MEMS inertial sensors is required. Two solutions are proposed: 1) The innovative Thermal Compensated Zero Velocity Update (TCZUPT) filter, which embeds the compensation of thermal effect on bias in the filter itself and uses Back-Propagation Neural Networks to build the calibration function. Experimental results show that the TCZUPT filter is faster than the traditional ZUPT filter in mapping significant bias variations and presents better performance in the overall testing period. Moreover, no calibration pre-processing stage is required to keep measurement drift under control, improving the accuracy, reliability, and maintainability of the processing software; 2) A redundant configuration of consumer grade inertial sensors to obtain a self-calibration of typical inertial sensors biases. The result is a significant reduction of uncertainty in attitude determination. In conclusion, both methods improve dead-reckoning performance for handling intermittent GNSS coverage. B. Proposing novel solutions for mission management to support the Unmanned Traffic Management (UTM) system in monitoring and coordinating the operations of a large number of UAS. Two solutions are proposed: 1) A trajectory prediction tool for small UAS, based on Learning Vector Quantization (LVQ) Neural Networks. By exploiting flight data collected when the UAS executes a pre-assigned flight path, the tool is able to predict the time taken to fly generic trajectory elements. Moreover, being self-adaptive in constructing a mathematical model, LVQ Neural Networks allow creating different models for the different UAS types in several environmental conditions; 2) A software tool aimed at supporting standardized procedures for decision-making process to identify UAS/payload configurations suitable for any type of mission that can be authorized standing flight regulations. The proposed methods improve the management and safe operation of large-scale UAS missions, speeding up the flight authorization process by the UTM system and supporting the increasing level of autonomy in UAS operations

Validation and Experimental Testing of Observers for Robust GNSS-Aided Inertial Navigation

This chapter is the study of state estimators for robust navigation. Navigation of vehicles is a vast field with multiple decades of research. The main aim is to estimate position, linear velocity, and attitude (PVA) under all dynamics, motions, and conditions via data fusion. The state estimation problem will be considered from two different perspectives using the same kinematic model. First, the extended Kalman filter (EKF) will be reviewed, as an example of a stochastic approach; second, a recent nonlinear observer will be considered as a deterministic case. A comparative study of strapdown inertial navigation methods for estimating PVA of aerial vehicles fusing inertial sensors with global navigation satellite system (GNSS)-based positioning will be presented. The focus will be on the loosely coupled integration methods and performance analysis to compare these methods in terms of their stability, robustness to vibrations, and disturbances in measurements

Analysis and enhancement of interpersonal coordination using inertial measurement unit solutions

Die heutigen mobilen Kommunikationstechnologien haben den Umfang der verbalen und textbasierten Kommunikation mit anderen Menschen, sozialen Robotern und künstlicher Intelligenz erhöht. Auf der anderen Seite reduzieren diese Technologien die nonverbale und die direkte persönliche Kommunikation, was zu einer gesellschaftlichen Thematik geworden ist, weil die Verringerung der direkten persönlichen Interaktionen eine angemessene Wahrnehmung sozialer und umgebungsbedingter Reizmuster erschweren und die Entwicklung allgemeiner sozialer Fähigkeiten bremsen könnte. Wissenschaftler haben aktuell die Bedeutung nonverbaler zwischenmenschlicher Aktivitäten als soziale Fähigkeiten untersucht, indem sie menschliche Verhaltensmuster in Zusammenhang mit den jeweilgen neurophysiologischen Aktivierungsmustern analzsiert haben. Solche Querschnittsansätze werden auch im Forschungsprojekt der Europäischen Union "Socializing sensori-motor contingencies" (socSMCs) verfolgt, das darauf abzielt, die Leistungsfähigkeit sozialer Roboter zu verbessern und Autismus-Spektrumsstörungen (ASD) adäquat zu behandeln. In diesem Zusammenhang ist die Modellierung und das Benchmarking des Sozialverhaltens gesunder Menschen eine Grundlage für theorieorientierte und experimentelle Studien zum weiterführenden Verständnis und zur Unterstützung interpersoneller Koordination. In diesem Zusammenhang wurden zwei verschiedene empirische Kategorien in Abhängigkeit von der Entfernung der Interagierenden zueinander vorgeschlagen: distale vs. proximale Interaktionssettings, da sich die Struktur der beteiligten kognitiven Systeme zwischen den Kategorien ändert und sich die Ebene der erwachsenden socSMCs verschiebt. Da diese Dissertation im Rahmen des socSMCs-Projekts entstanden ist, wurden Interaktionssettings für beide Kategorien (distal und proximal) entwickelt. Zudem wurden Ein-Sensor-Lösungen zur Reduzierung des Messaufwands (und auch der Kosten) entwickelt, um eine Messung ausgesuchter Verhaltensparameter bei einer Vielzahl von Menschen und sozialen Interaktionen zu ermöglichen. Zunächst wurden Algorithmen für eine kopfgetragene Trägheitsmesseinheit (H-IMU) zur Messung der menschlichen Kinematik als eine Ein-Sensor-Lösung entwickelt. Die Ergebnisse bestätigten, dass die H-IMU die eigenen Gangparameter unabhängig voneinander allein auf Basis der Kopfkinematik messen kann. Zweitens wurden—als ein distales socSMC-Setting—die interpersonellen Kopplungen mit einem Bezug auf drei interagierende Merkmale von „Übereinstimmung“ (engl.: rapport) behandelt: Positivität, gegenseitige Aufmerksamkeit und Koordination. Die H-IMUs überwachten bestimmte soziale Verhaltensereignisse, die sich auf die Kinematik der Kopforientierung und Oszillation während des Gehens und Sprechens stützen, so dass der Grad der Übereinstimmung geschätzt werden konnte. Schließlich belegten die Ergebnisse einer experimentellen Studie, die zu einer kollaborativen Aufgabe mit der entwickelten IMU-basierten Tablet-Anwendung durchgeführt wurde, unterschiedliche Wirkungen verschiedener audio-motorischer Feedbackformen für eine Unterstützung der interpersonellen Koordination in der Kategorie proximaler sensomotorischer Kontingenzen. Diese Dissertation hat einen intensiven interdisziplinären Charakter: Technologische Anforderungen in den Bereichen der Sensortechnologie und der Softwareentwicklung mussten in direktem Bezug auf vordefinierte verhaltenswissenschaftliche Fragestellungen entwickelt und angewendet bzw. gelöst werden—und dies in zwei unterschiedlichen Domänen (distal, proximal). Der gegebene Bezugsrahmen wurde als eine große Herausforderung bei der Entwicklung der beschriebenen Methoden und Settings wahrgenommen. Die vorgeschlagenen IMU-basierten Lösungen könnten dank der weit verbreiteten IMU-basierten mobilen Geräte zukünftig in verschiedene Anwendungen perspektiv reich integriert werden.Today’s mobile communication technologies have increased verbal and text-based communication with other humans, social robots and intelligent virtual assistants. On the other hand, the technologies reduce face-to-face communication. This social issue is critical because decreasing direct interactions may cause difficulty in reading social and environmental cues, thereby impeding the development of overall social skills. Recently, scientists have studied the importance of nonverbal interpersonal activities to social skills, by measuring human behavioral and neurophysiological patterns. These interdisciplinary approaches are in line with the European Union research project, “Socializing sensorimotor contingencies” (socSMCs), which aims to improve the capability of social robots and properly deal with autism spectrum disorder (ASD). Therefore, modelling and benchmarking healthy humans’ social behavior are fundamental to establish a foundation for research on emergence and enhancement of interpersonal coordination. In this research project, two different experimental settings were categorized depending on interactants’ distance: distal and proximal settings, where the structure of engaged cognitive systems changes, and the level of socSMCs differs. As a part of the project, this dissertation work referred to this spatial framework. Additionally, single-sensor solutions were developed to reduce costs and efforts in measuring human behaviors, recognizing the social behaviors, and enhancing interpersonal coordination. First of all, algorithms using a head worn inertial measurement unit (H-IMU) were developed to measure human kinematics, as a baseline for social behaviors. The results confirmed that the H-IMU can measure individual gait parameters by analyzing only head kinematics. Secondly, as a distal sensorimotor contingency, interpersonal relationship was considered with respect to a dynamic structure of three interacting components: positivity, mutual attentiveness, and coordination. The H-IMUs monitored the social behavioral events relying on kinematics of the head orientation and oscillation during walk and talk, which can contribute to estimate the level of rapport. Finally, in a new collaborative task with the proposed IMU-based tablet application, results verified effects of different auditory-motor feedbacks on the enhancement of interpersonal coordination in a proximal setting. This dissertation has an intensive interdisciplinary character: Technological development, in the areas of sensor and software engineering, was required to apply to or solve issues in direct relation to predefined behavioral scientific questions in two different settings (distal and proximal). The given frame served as a reference in the development of the methods and settings in this dissertation. The proposed IMU-based solutions are also promising for various future applications due to widespread wearable devices with IMUs.European Commission/HORIZON2020-FETPROACT-2014/641321/E

The use of inertial measurement units for the determination of gait spatio-temporal parameters

The aim of this work was to develop a methodology whereby inertial measurement units (IMUs) could be used to obtain accurate and objective gait parameters within typical developed adults (TDA) and Parkinson’s disease (PD). The thesis comprised four studies, the first establishing the validity of the IMU method when measuring the vertical centre of mass (CoM) acceleration, velocity and position versus an optical motion capture system (OMCS) in TDA. The second study addressed the validity of the IMU and inverted pendulum model measurements within PD and also explored the inter-rater reliability of the measurement. In the third study the optimisation of the inverted pendulum model driven by IMU data was explored when comparing to standardised clinical tests within TDA and PD, and the fourth explored a novel phase plot analysis applied to CoM movement to explore gait in more detail. The validity study showed no significant difference for vertical acceleration and position between IMU and OMCS measurements within TDA. Vertical velocity however did show a significant difference, but the error was still less than 2.5%. ICCs for all three parameters ranged from 0.782 to 0.952, indicating an adequate test-retest reliability. Within PD there was no significant difference found for vertical CoM acceleration, velocity and position. ICCs for all three parameters ranged from 0.77 to 0.982. In addition, the reliability calculations found no difference for step time, stride length and walking speed for people with PD. Inter-rater reliability was found not to be different for the same parameters. The optimisation of the correction factor when using the inverted pendulum model showed no significant difference between TDA and PD. Furthermore the correction factor was found not to be related to walking speed. The fourth and final study found that phase plot analysis of variability could be performed on CoM vertical excursion. TDA and PD were shown to have, on average, different characteristics. This thesis demonstrated that CoM motion can be objectively measured within a clinical setting in people with PD by utilizing IMUs. Furthermore, in depth gait variability analysis can be performed by utilizing a phase plot method

INERTIAL MOTION CAPTURE SYSTEM FOR BIOMECHANICAL ANALYSIS IN PRESSURE SUITS

A non-invasive system has been developed at the University of Maryland Space System Laboratory with the goal of providing a new capability for quantifying the motion of the human inside a space suit. Based on an array of six microprocessors and eighteen microelectromechanical (MEMS) inertial measurement units (IMUs), the Body Pose Measurement System (BPMS) allows the monitoring of the kinematics of the suit occupant in an unobtrusive, self-contained, lightweight and compact fashion, without requiring any external equipment such as those necessary with modern optical motion capture systems. BPMS measures and stores the accelerations, angular rates and magnetic fields acting upon each IMU, which are mounted on the head, torso, and each segment of each limb. In order to convert the raw data into a more useful form, such as a set of body segment angles quantifying pose and motion, a series of geometrical models and a non-linear complimentary filter were implemented. The first portion of this works focuses on assessing system performance, which was measured by comparing the BPMS filtered data against rigid body angles measured through an external VICON optical motion capture system. This type of system is the industry standard, and is used here for independent measurement of body pose angles. By comparing the two sets of data, performance metrics such as BPMS system operational conditions, accuracy, and drift were evaluated and correlated against VICON data. After the system and models were verified and their capabilities and limitations assessed, a series of pressure suit evaluations were conducted. Three different pressure suits were used to identify the relationship between usable range of motion and internal suit pressure. In addition to addressing range of motion, a series of exploration tasks were also performed, recorded, and analysed in order to identify different motion patterns and trajectories as suit pressure is increased and overall suit mobility is reduced. The focus of these evaluations was to quantify the reduction in mobility when operating in any of the evaluated pressure suits. This data should be of value in defining new low cost alternatives for pressure suit performance verification and evaluation. This work demonstrates that the BPMS technology is a viable alternative or companion to optical motion capture; while BPMS is the first motion capture system that has been designed specifically to measure the kinematics of a human in a pressure suit, its capabilities are not constrained to just being a measurement tool. The last section of the manuscript is devoted to future possible uses for the system, with a specific focus on pressure suit applications such in the use of BPMS as a master control interface for robot teleoperation, as well as an input interface for future robotically augmented pressure suits

Characterizing the Variability of Kinematic Outcome Measures and Compensatory Movements using Inertial Measurement Units

Cost-effective wearable sensors to measure movement have gained traction as research and clinical tools. The potential to quantify movement with a portable and inexpensive way could provide benefits to patient populations (e.g. amputees) to supplement or replace current clinical evaluations. For example, characterization of frontal plane kinematic outcome measures is a relevant movement pattern to a complex amputee population. The ability to capture such movements could have important therapeutic opportunities. The current research worked towards characterizing frontal plane compensatory movement patterns with kinematic outcome measures described by inertial measurement units (IMU) data in healthy adults. This was an initial step towards developing a future toolkit that could characterize normal and aberrant movement patterns in clinical populations. The thesis is comprised of two related studies. The first study set out to evaluate the numerical accuracy of IMU estimated spatial measures when compared to a gold standard system. Six subjects completed six different movement tasks while instrumented with optical motion capture and IMUs. Each movement task probed the accuracy of specific deviations (e.g. vertical deviation). The hypothesis was that outcome measures would be strongly associated (r>0.8) and mean error would not be significantly different from zero and the coefficient of repeatability would be within priori set limits of agreement (±18 mm). Kinematic outcome measures had small mean error bias compared to gold standard measures and range of subject specific mean errors showed minimal differences. Task specific differences were evident when movement patterns exhibit large transverse rotations. These results showed the devices have a level of accuracy that may be suitable to characterize changes in movement patterns clinically. The second study aimed to utilize the same techniques from study 1 to describe compensatory kinematic outcome measures during a clinical obstacle avoidance task to differentiate between compensatory and normal movement patterns. Twelve subjects wore IMUs bilaterally on the ankles and on the belt above the right hip. An off the shelf orthotic knee brace was used to restrict lower limb knee joint kinematics (reduce range of motion). Participants completed 15 walking trials for three different brace conditions (No Brace, Unlocked Brace, Locked Brace) and two obstacle task conditions (Level Ground Walking and Obstacle Avoidance) to elicit a comparison of normal and compensatory movements. During the walking task, IMUs were able to characterize compensatory movements typical of the amputee population. Lateral deviation of the swinging foot was significantly larger during obstacle crossing with a locked brace compared to no brace. Maximum elevation of the limb was significantly larger while crossing obstacles compared to level ground walking and was precise enough to discern elevation differences of No Brace elevation from both Unlocked and Locked Brace conditions. Hip hiking was also significantly larger in the locked brace obstacle crossing from no brace obstacle crossing. Swing time was longer when the limb was braced and during obstacle crossing when compared to level ground walking. Healthy subjects had no significant changes to double support time compared those exhibited by amputees during walking. Overall, differences between IMU and gold standard measures are present. Mean error differences are present for certain tasks and criteria for agreeability between devices is not satisfied. Descriptive analysis of low subject mean error ranges across the majority of tasks indicate a potential utility in these measures to distinguish between movement patterns. During the clinical task, when knee mobility was manipulated compensatory movements were significantly different across conditions. This study provides evidence for the utility of IMU devices to support clinical gait analysis with quantifiable measures

Addressing the problem of Interaction in fully immersive Virtual Environments: from raw sensor data to effective devices

Immersion into Virtual Reality is a perception of being physically present in a non-physical world. The perception is created by surrounding the user of the VR system with images, sound or other stimuli that provide an engrossing total environment. The use of technological devices such as stereoscopic cameras, head-mounted displays, tracking systems and haptic interfaces allows for user experiences providing a physical feeling of being in a realistic world, and the term “immersion” is a metaphoric use of the experience of submersion applied to representation, fiction or simulation. One of the main peculiarity of fully immersive virtual reality is the enhancing of the simple passive viewing of a virtual environment with the ability to manipulate virtual objects inside it. This Thesis project investigates such interfaces and metaphors for the interaction and the manipulation tasks. In particular, the research activity conducted allowed the design of a thimble-like interface that can be used to recognize in real-time the human hand’s orientation and infer a simplified but effective model of the relative hand’s motion and gesture. Inside the virtual environment, users provided with the developed systems will be therefore able to operate with natural hand gestures in order to interact with the scene; for example, they could perform positioning task by moving, rotating and resizing existent objects, or create new ones from scratch. This approach is particularly suitable when there is the need for the user to operate in a natural way, performing smooth and precise movements. Possible applications of the system to the industry are the immersive design in which the user can perform Computer- Aided Design (CAD) totally immersed in a virtual environment, and the operators training, in which the user can be trained on a 3D model in assembling or disassembling complex mechanical machineries, following predefined sequences. The thesis has been organized around the following project plan: - Collection of the relevant State Of The Art - Evaluation of design choices and alternatives for the interaction hardware - Development of the necessary embedded firmware - Integration of the resulting devices in a complex interaction test-bed - Development of demonstrative applications implementing the device - Implementation of advanced haptic feedbac