Potential of mobile applications in human-centric production and logistics management

With the increasing market penetration of smart devices (smartphones, smartwatches, and tablets), various mobile applications (apps) have been developed to fulfill tasks in daily life. Recently, efforts have been made to develop apps to support human operators in industrial work. When apps installed on commercial devices are utilized, tasks that were formerly done purely manually or with the help of investment-intensive specific devices can be performed more efficiently and/or at a lower cost and with reduced errors. Despite their advantages, smart devices have limitations because embedded sensors (e.g., accelerometers) and components (e.g., cameras) are usually designed for nonindustrial use. Hence, validation experiments and case studies for industrial applications are needed to ensure the reliability of app usage. In this study, a systematic literature review was employed to identify the state of knowledge about the use of mobile apps in production and logistics management. The results show how apps can support human centricity based on the enabling technologies and components of smart devices. An outlook for future research and applications is provided, including the need for proper validation studies to ensure the diversity and reliability of apps and more research on psychosocial aspects of human-technology interaction

FPGA-Based Fused Smart Sensor for Dynamic and Vibration Parameter Extraction in Industrial Robot Links

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA)

Estimating the orientation of a game controller from inertial and magnetic measurements

L’estimation de l’orientation d’un corps rigide en mouvement dans l’espace joue un rôle indispensable dans les technologies de navigation, par exemple, les systèmes militaires de missiles, les avions civils, les systèmes de navigation chirurgicale, la cartographie faite par des robots, les véhicules autonomes et les contrôleurs de jeux. Cette technique est maintenant utilisée dans certaines applications qui nous touchent directement, notamment dans les contrôleurs de jeux tels que la Wii-mote. Dans cette veine, la recherche présentée ici porte sur l’estimation de l’orientation d’un corps rigide à partir des mesures de capteurs inertiels et magnétiques peu coûteux. Comme les capteurs inertiels permettent de mesurer les dérivées temporelles de l’orientation, il est naturel de commencer par l’estimation de la vitesse angulaire. Par conséquent, nous présentons d’abord une nouvelle façon de déterminer la vitesse angulaire d’un corps rigide à partir d’accéléromètres. Ensuite, afin d’estimer l’orientation, nous proposons une nouvelle méthode d’estimation de l’orientation d’un corps rigide dans le plan vertical à partir des mesures d’accéléromètres, en discernant ses composantes inertielle et gravitationnelle. Mais, ce n’est sûrement pas suffisant d’estimer l’orientation dans le plan vertical, parce que la plupart des applications se produisent dans l’espace tridimensionnel. Pour estimer les rotations dans l’espace, nous présentons d’abord la conception d’un contrôleur de jeu, dans lequel tous les capteurs nécessaires sont installés. Ensuite, ces capteurs sont étalonnés pour déterminer leurs facteurs d’échelle et leurs zéros, de manière à améliorer leurs exactitudes. Ensuite, nous développons une nouvelle méthode d’estimation de l’orientation d’un corps rigide se déplaçant dans l’espace, encore en discernant les composantes gravitationnelle et inertielle des accélérations. Finalement, pour imiter le contrôleur de jeu Wii, nous créons une interface usager simple de sorte qu’une représentation virtuelle du contrôleur de jeu puisse suivre chaque mouvement du contrôleur de jeu conçu (réalité virtuelle). L’interface usager conçue montre que l’algorithme proposé est suffisamment précis pour donner à l’usager un contrôle fidèle de l’orientation du contrôleur de jeu virtuel.Estimating the orientation of a rigid-body moving in space is an indispensable component of navigation technology, e.g., military missile systems, civil aircrafts, surgical navigation systems, robot mapping, autonomous vehicles and game controllers. It has now come directly into some aspects of our lives, notoriously in game controllers, such as the Wiimote. In this vein, this research focuses on the development of new algorithms to estimate the rigid-body orientation from common inexpensive inertial and magnetic sensors. As inertial sensors measure the time derivatives of the orientation, it is natural to start with the estimation of the angular velocity. More precisely, we present a novel way of determining the angular velocity of a rigid body from accelerometer measurements. This method finds application in crashworthiness and motion analysis in sports, for example, where impacts forbid the use of mechanical gyroscopes. Secondly, in an attempt to estimate the orientation in a simplified setting, we propose a novel method of estimating the orientation of a rigid body in the vertical plane from point-acceleration measurements, by discerning its gravitational and inertial components. Thirdly, it is surely not enough to estimate the orientation in the vertical plane, because most applications take place in three dimensions. For estimating rotations in space, we first present the game controller design, in which all necessary sensors are installed. Then, these sensors are calibrated to determine their scale factors and offsets so as to improve their performances. Thence, we develop a novel method of estimating the orientation of a rigid body moving in space from inertial sensors, also by discerning the gravitational and inertial components of the acceleration. Finally, in order to imitate the game controller Wii, we create a simple user interface in which a virtual representative of the game controller follows every orientation of the true game controller (virtual reality). The user interface shows that the proposed algorithm is sufficiently accurate to give the user a transparent control of the orientation of the virtual game controller

Multimodal, Embodied and Location-Aware Interaction

This work demonstrates the development of mobile, location-aware, eyes-free applications which utilise multiple sensors to provide a continuous, rich and embodied interaction. We bring together ideas from the fields of gesture recognition, continuous multimodal interaction, probability theory and audio interfaces to design and develop location-aware applications and embodied interaction in both a small-scale, egocentric body-based case and a large-scale, exocentric `world-based' case. BodySpace is a gesture-based application, which utilises multiple sensors and pattern recognition enabling the human body to be used as the interface for an application. As an example, we describe the development of a gesture controlled music player, which functions by placing the device at different parts of the body. We describe a new approach to the segmentation and recognition of gestures for this kind of application and show how simulated physical model-based interaction techniques and the use of real world constraints can shape the gestural interaction. GpsTunes is a mobile, multimodal navigation system equipped with inertial control that enables users to actively explore and navigate through an area in an augmented physical space, incorporating and displaying uncertainty resulting from inaccurate sensing and unknown user intention. The system propagates uncertainty appropriately via Monte Carlo sampling and output is displayed both visually and in audio, with audio rendered via granular synthesis. We demonstrate the use of uncertain prediction in the real world and show that appropriate display of the full distribution of potential future user positions with respect to sites-of-interest can improve the quality of interaction over a simplistic interpretation of the sensed data. We show that this system enables eyes-free navigation around set trajectories or paths unfamiliar to the user for varying trajectory width and context. We demon- strate the possibility to create a simulated model of user behaviour, which may be used to gain an insight into the user behaviour observed in our field trials. The extension of this application to provide a general mechanism for highly interactive context aware applications via density exploration is also presented. AirMessages is an example application enabling users to take an embodied approach to scanning a local area to find messages left in their virtual environment

Multimodal, Embodied and Location-Aware Interaction

This work demonstrates the development of mobile, location-aware, eyes-free applications which utilise multiple sensors to provide a continuous, rich and embodied interaction. We bring together ideas from the fields of gesture recognition, continuous multimodal interaction, probability theory and audio interfaces to design and develop location-aware applications and embodied interaction in both a small-scale, egocentric body-based case and a large-scale, exocentric `world-based' case. BodySpace is a gesture-based application, which utilises multiple sensors and pattern recognition enabling the human body to be used as the interface for an application. As an example, we describe the development of a gesture controlled music player, which functions by placing the device at different parts of the body. We describe a new approach to the segmentation and recognition of gestures for this kind of application and show how simulated physical model-based interaction techniques and the use of real world constraints can shape the gestural interaction. GpsTunes is a mobile, multimodal navigation system equipped with inertial control that enables users to actively explore and navigate through an area in an augmented physical space, incorporating and displaying uncertainty resulting from inaccurate sensing and unknown user intention. The system propagates uncertainty appropriately via Monte Carlo sampling and output is displayed both visually and in audio, with audio rendered via granular synthesis. We demonstrate the use of uncertain prediction in the real world and show that appropriate display of the full distribution of potential future user positions with respect to sites-of-interest can improve the quality of interaction over a simplistic interpretation of the sensed data. We show that this system enables eyes-free navigation around set trajectories or paths unfamiliar to the user for varying trajectory width and context. We demon- strate the possibility to create a simulated model of user behaviour, which may be used to gain an insight into the user behaviour observed in our field trials. The extension of this application to provide a general mechanism for highly interactive context aware applications via density exploration is also presented. AirMessages is an example application enabling users to take an embodied approach to scanning a local area to find messages left in their virtual environment

Kinematic and Dynamic Study of Cam Mechanisms for Bottling Machines

The main objective of this study is to analyze and optimize the cam mechanisms of the cork capper station currently in use for wine bottling machines. For each machine model considered, current cam profiles and corresponding real trajectories performed during operation are analyzed. Subsequently, various alternative laws of motion are tested to implement the same process, respecting the same precision points but modifying other parts of trajectory to improve machine dynamic performances. A series of tests carried out on a reconfigurable prototype and using different types of cork have made it possible to verify the effectiveness of the new laws of motion and to obtain the load acting on the machine at different operating speeds

On the predictability of time series by metric entropy

Thesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2006Includes bibliographical references (leaves: 48-49)Text in English; Abstract: Turkish and Englishxi, 55 leavesThe computation of the metric entropy, a measure of the loss of information along the attractor, from experimental time series is the main objective of this study. In this study, replacing the current warning systems (simple threshold based, on/off circuits), a new and promising prognosis system is tried to be achieved by the metric entropy, i.e. Kolmogorov . Sinai entropy, from chaotic time series. Additional to metric entropy, correlation dimension and time series statistical parameters were investigated.Condition monitoring of ball bearings and drill bits was achieved in the light of practical considerations of time series applications. Two different accelerated bearing run-to-failure test rigs were constructed and the prediction tests were performed.However, as a reason of shaft failure in both structures during the experiments, none of them is completed. Finally, drill bit breakage experiments were carried out. In the experiments, 10 small drill bits (1 mm ) were tested until they broke down, while vibration data were consecutively taken in equal time intervals. After the analysis, a consistent decrement in variation of metric entropy just before the breakage was observed. As a result of the experiment results, metric entropy variation could be proposed as an early warning system

Enabling Human-Robot Collaboration via Holistic Human Perception and Partner-Aware Control

As robotic technology advances, the barriers to the coexistence of humans and robots are slowly coming down. Application domains like elderly care, collaborative manufacturing, collaborative manipulation, etc., are considered the need of the hour, and progress in robotics holds the potential to address many societal challenges. The future socio-technical systems constitute of blended workforce with a symbiotic relationship between human and robot partners working collaboratively. This thesis attempts to address some of the research challenges in enabling human-robot collaboration. In particular, the challenge of a holistic perception of a human partner to continuously communicate his intentions and needs in real-time to a robot partner is crucial for the successful realization of a collaborative task. Towards that end, we present a holistic human perception framework for real-time monitoring of whole-body human motion and dynamics. On the other hand, the challenge of leveraging assistance from a human partner will lead to improved human-robot collaboration. In this direction, we attempt at methodically defining what constitutes assistance from a human partner and propose partner-aware robot control strategies to endow robots with the capacity to meaningfully engage in a collaborative task

Instationary modal Analysis for Impulse-type stimulated structures

In order to determine modal parameters, classical experimental modal analysis can be used in engineering application. This method finds a system frequency response function using fast Fourier Transform (FFT). The Fourier Transform is one type of global data analysis method. The frequency resolution is equal to the reciprocal of the total sample time. So applying the FFT is not suitable for any transient signal to reveal local characteristics. However, in modern manufacturing industries, processing forces are rapidly changing. The dynamic behavior may vary rapidly in a short time due to variations in the machining parameters and changes in boundary conditions. These nonlinear and non-stationary dynamic parameters are not constant during machining operations identification using FFT. In this research, an innovative transient signal analysis approach has been developed, which is based on an application of the least squares estimation. The proposed method provides transient information with high resolution and to identify the time-varying modal parameters during machining. Least squares estimation can be augmented with a sliding-window operation (SWLSE) to reveal the actual system dynamic behavior at any moment. The accuracy of this method depends on the window size, the noise ratio and the sampling rate etc. The estimation accuracy of modal parameters is discussed in this work. To examine the efficiency of the SWLSE method experimental tests are performed on a laboratory beam system and the results are compared with the classical experimental modal analysis (CEMA) method. The laboratory beam system is designed and assembled that the stiffness and damping ratio of the structure can be adjusted. Additionally, the proposed method is applied to the identification of the actual modal parameters of machine tools during machining operations. In another application, the proposed method provides also the process varied damping information in a process monitoring