Objekt-Manipulation und Steuerung der Greifkraft durch Verwendung von Taktilen Sensoren

This dissertation describes a new type of tactile sensor and an improved version of the dynamic tactile sensing approach that can provide a regularly updated and accurate estimate of minimum applied forces for use in the control of gripper manipulation. The pre-slip sensing algorithm is proposed and implemented into two-finger robot gripper. An algorithm that can discriminate between types of contact surface and recognize objects at the contact stage is also proposed. A technique for recognizing objects using tactile sensor arrays, and a method based on the quadric surface parameter for classifying grasped objects is described. Tactile arrays can recognize surface types on contact, making it possible for a tactile system to recognize translation, rotation, and scaling of an object independently.Diese Dissertation beschreibt eine neue Art von taktilen Sensoren und einen verbesserten Ansatz zur dynamischen Erfassung von taktilen daten, der in regelmäßigen Zeitabständen eine genaue Bewertung der minimalen Greifkraft liefert, die zur Steuerung des Greifers nötig ist. Ein Berechnungsverfahren zur Voraussage des Schlupfs, das in einen Zwei-Finger-Greifarm eines Roboters eingebaut wurde, wird vorgestellt. Auch ein Algorithmus zur Unterscheidung von verschiedenen Oberflächenarten und zur Erkennung von Objektformen bei der Berührung wird vorgestellt. Ein Verfahren zur Objekterkennung mit Hilfe einer Matrix aus taktilen Sensoren und eine Methode zur Klassifikation ergriffener Objekte, basierend auf den Daten einer rechteckigen Oberfläche, werden beschrieben. Mit Hilfe dieser Matrix können unter schiedliche Arten von Oberflächen bei Berührung erkannt werden, was es für das Tastsystem möglich macht, Verschiebung, Drehung und Größe eines Objektes unabhängig voneinander zu erkennen

A differential-based parallel force/velocity actuation concept : theory and experiments

textRobots are now moving from their conventional confined habitats such as factory floors to human environments where they assist and physically interact with people. The requirement for inherent mechanical safety is overarching in such human-robot interaction systems. We propose a dual actuator called Parallel Force/Velocity Actuator (PFVA) that combines a Force Actuator (FA) (low velocity input) and a Velocity Actuator (VA) (high velocity input) using a differential gear train. In this arrangement mechanical safety can be achieved by limiting the torque on the FA and thus making it a backdriveable input. In addition, the kinematic redundancy in the drive can be used to control output velocity while satisfying secondary operational objectives. Our research focus was on three areas: (i) scalable parametric design of the PFVA, (ii) analytical modeling of the PFVA and experimental testing on a single-joint prototype, and (iii) generalized model formulation for PFVA-driven serial robot manipulators. In our analysis, the ratio of velocity ratios between the FA and the VA, called the relative scale factor, emerged as a purely geometric and dominant design parameter. Based on a dimensionless parametric design of PFVAs using power-flow and load distributions between the inputs, a prototype was designed and built using commercial-off-the-shelf components. Using controlled experiments, two performance-limiting phenomena in our prototype, friction and dynamic coupling between the two inputs, were identified. Two other experiments were conducted to characterize the operational performance of the actuator in velocity-mode and in what we call ‘torque-limited’ mode (i.e. when the FA input can be backdriven). Our theoretical and experimental results showed that the PFVA can be mechanical safe to both slow collisions and impacts due to the backdriveability of the FA. Also, we show that its kinematic redundancy can be effectively utilized to mitigate low-velocity friction and backlash in geared mechanisms. The implication at the system level of our actuator level analytical and experimental work was studied using a generalized dynamic modeling framework based on kinematic influence coefficients. Based on this dynamic model, three design case studies for a PFVA-driven serial planar 3R manipulator were presented. The major contributions of this research include (i) mathematical models and physical understanding for over six fundamental design and operational parameters of the PFVA, based on which approximately ten design and five operational guidelines were laid out, (ii) analytical and experimental proof-of-concept for the mechanical safety feature of the PFVA and the effective utilization of its kinematic redundancy, (iii) an experimental methodology to characterize the dynamic coupling between the inputs in a differential-summing mechanism, and (iv) a generalized dynamic model formulation for PFVA-driven serial robot manipulators with emphasis on distribution of output loads between the FA and VA input-sets.Mechanical Engineerin

TACTILE SENSING WITH COMPLIANT STRUCTURES FOR HUMAN-ROBOT INTERACTION

This dissertation presents the research on tactile sensing with compliant structures towards human-robot interaction. It would be beneficial for robots working collaboratively with humans to be soft or padded and have compliant tactile sensing skins over the padding. To allow the robots to interact with humans via touch effectively and safely and to detect tactile stimuli in an unstructured environment, new tactile sensing concepts are needed that can detect a wide range of potential interactions and sense over an area. However, most highly sensitive tactile sensors are unable to cover the forces involved in human contacts, which ranges from 1 newton to thousand newtons; to implement area sensing capabilities, there have been challenges in creating traditional sensing arrays, where the associated supporting electronics become more complex with an increasing number of sensing elements. This dissertation develops a novel multi-layer cutaneous tactile sensing architecture for enhanced sensitivity and range, and employs an imaging technique based on boundary measurements called electrical impedance tomography (EIT) to achieve area tactile sensing capabilities. The multi-layer cutaneous tactile sensing architecture, which consists of stretchable piezoresistive strain-sensing layers over foam padding layers of different stiffness, allows for both sufficient sensitivity and an extended force range for human contacts. The role that the padding layer plays when placed under a stretchable sensing layer was investigated, and it was discovered that the padding layer magnifies the sensor signal under indentation compared to that obtained without padding layers. The roles of the multi-layer foams were investigated by changing stiffness and thickness, which allows tailoring the response of multi-layer architectures for different applications. To achieve both extended force range and distributed sensing, EIT technique was employed with the multi-layer sensing architecture. Machine and human touch were conducted on the developed multi-layer sensing system, revealing that the second sensing skin is required to detect the large variability in human touch. Although widely applied in the medical field for functional imaging, EIT applied in tactile sensing faces different challenges, such as unknown number and region of tactile stimuli. Current EIT tactile sensors have focused on qualitative demonstration. This dissertation aims at achieving quantitative information from piezoresistive EIT tactile sensors, by investigating spatial performance and the effect of sensor’s conductivity. A spatial correction method was developed for obtaining consistent spatial information, which was validated by both simulation and experiments from our stretchable piezoresistive EIT sensor with an underlying padding layer

Artificial Skin in Robotics

Artificial Skin - A comprehensive interface for system-environment interaction - This thesis investigates a multifunctional artificial skin as touch sensitive whole-body cover for robotic systems. To further the evolution from tactile sensors to an implementable artificial skin a general concept for the design process is derived. A standard test procedure is proposed to evaluate the performance. The artificial skin contributes to a safe and intuitive physical human robot interaction

Sensitive Skin for Robotics

This thesis explores two novel ways of reducing the data complexity of tactile sensing. The thesis begins by examining the state-of-the art in tactile sensing, not only examining the sensor construction and interpretation of data but also the motivation for these designs. The thesis then proposes two methods for reducing the complexity of data in tactile sensing. The first is a low-power tactile sensing array exploiting a novel application of a pressure-sensitive material called quantum tunnelling composite. The properties of this material in this array form are shown to be beneficial in robotics. The electrical characteristics of the material are also explored. A bit-based structure for representing tactile data called Bitworld is then defined and its computational performance is characterised. It is shown that this bit-based structure outperforms floating-point arrays by orders of magnitude. This structure is then shown to allow high-resolution images to be produced by combining low resolution sensor arrays with equivalent functional performance to a floating-point array, but with the advantages of computational efficiency. Finally, an investigation into making Bitworld robust in the presence of positional noise is described with simulations to verify that such robustness can be achieved. Overall, the sensor and data structure described in this thesis allow simple, but effective tactile systems to be deployed in robotics without requiring a significant commitment of computational or power resources on the part of a robot designer.EThOS - Electronic Theses Online ServiceGBUnited Kingdo